Online research in philosophy

An application of the Method of Analysis of Relational Complexity (MARC) to suppositional reasoning in the knight-knave task is outlined. The task requires testing suppositions derived from statements made by individuals who either always tell the truth or always lie. Relational complexity (RC) is defined as the number of unique entities that need to be processed in parallel to arrive at a solution. A selection of five ternary and five quaternary items were presented to 53 psychology (...) students using a pencil and paper format. A computer-administered version was presented to 50 students. As predicted, quaternary problems were associated with higher error rates and longer response times than ternary problems. The computer-administered form was more difficult than the pencil and paper version of the test. These differences are discussed in terms of RC theory and alternative processing accounts. Together, they indicate that the relational complexity metric is a useful and parsimonious way to quantify complexity of reasoning tasks. (shrink)

The confusion/non-consequential thinking explanation proposed by Newstead, Girotto, and Legrenzi (1995) for poor performance on Wason's THOG problem (a hypothetico-deductive reasoning task) was examined in three experiments with 300 participants. In general, as the cognitive complexity of the problem and the possibility of non-consequential thinking were reduced, correct performance increased. Significant but weak facilitation (33-40% correct) was found in Experiment 1 for THOG classification instructions that did not include the indeterminate response option. Substantial facilitation (up to 75% correct) (...) was obtained in Experiment 2 with O'Brien et al.'s (1990) one-other-THOG classification instruction. In Experiment 3, a revised version of O'Brien et al.'s pre-test problem format also led to substantial facilitation, even with the use of the standard three-choice THOG classification instruction. These findings are discussed in terms of Newstead et al.'s theoretical proposal and possible attentional factors. (shrink)

We discuss how modified dual-task approaches may be used to verify the degree to which cognitive tasks are capacity demanding. We also delineate some of the complexities associated with the use of the “double easy-to-hard” paradigm for testing claim of Halford, Wilson & Phillips that hierarchical reasoning imposes processing demands equivalent to those of transitive reasoning.

In this study both adolescents with autism spectrum disorder (ASD) and typically developing controls were presented with conditional reasoning problems using familiar content. In this task both valid and fallacious conditional inferences that would otherwise be drawn can be suppressed if counterexample cases are brought to mind. Such suppression occurs when additional premises are presented, whose effect is to suggest such counterexample cases. In this study we predicted and observed that this suppression effect was substantially and significantly weaker for (...) autistic participants. We take this as evidence that autistics are less contextualised in their reasoning, a finding that can be linked to research on autism on a variety of other cognitive tasks. (shrink)

The core issue of our target article concerns how relational complexity should be assessed. We propose that assessments must be based on actual cognitive processes used in performing each step of a task. Complexity comparisons are important for the orderly interpretation of research findings. The links between relational complexity theory and several other formulations, as well as its implications for neural functioning, connectionist models, the roles of knowledge, and individual and developmental differences, are considered.

This article discusses how sequential sampling models can be integrated in a cognitive architecture. The new theory Retrieval by Accumulating Evidence in an Architecture (RACE/A) combines the level of detail typically provided by sequential sampling models with the level of task complexity typically provided by cognitive architectures. We will use RACE/A to model data from two variants of a picture–word interference task in a psychological refractory period design. These models will demonstrate how RACE/A enables interactions between sequential (...) sampling and long-term declarative learning, and between sequential sampling and task control. In a traditional sequential sampling model, the onset of the process within the task is unclear, as is the number of sampling processes. RACE/A provides a theoretical basis for estimating the onset of sequential sampling processes during task execution and allows for easy modeling of multiple sequential sampling processes within a task. (shrink)

Measurements of the dimensionality of chaotic attractors obtained on behavioral data represent the task complexity and also could be hypothesized to reflect the number of synchronized neural groups involved in the generation of the data. The changes in dimensionality for different experimental conditions suggest that limited processing capacity, task complexity, demand, and synchrony in neural firing might be closely related.

bruce@edmonds.name http://bruce.edmonds.name Abstract. Two kinds of problem are distinguished: the first of finding processes which produce complex outcomes from the interaction of simple parts, and the second of finding which process resulted in an observed complex outcome. The former I call the easy complexity problem and the later the hard complexity problem. It is often assumed that progress with the easy problem will aid process with the hard problem. However this assumes that the “reverse engineering” problem, of determining (...) the process from the outcomes is feasible. Taking a couple of simple models of reverse engineering, I show that this task is infeasible in the general case. Hence it cannot be assumed that reverse engineering is possible, and hence that most of the time progress on the easy problem will not help with the hard problem unless there are special properties of a particular set of processes that make it feasible. Assuming that complexity science is not merely an academic “game” and given the analysis of this paper, some criteria for the kinds of paper that have a reasonable chance of being eventually useful for understanding observed complex systems are outlined. Many complexity papers do not fare well against these critieria. (shrink)

In the dissertation we study the complexity of generalized quantifiers in natural language. Our perspective is interdisciplinary: we combine philosophical insights with theoretical computer science, experimental cognitive science and linguistic theories. -/- In Chapter 1 we argue for identifying a part of meaning, the so-called referential meaning (model-checking), with algorithms. Moreover, we discuss the influence of computational complexity theory on cognitive tasks. We give some arguments to treat as cognitively tractable only those problems which can be computed in (...) polynomial time. Additionally, we suggest that plausible semantic theories of the everyday fragment of natural language can be formulated in the existential fragment of second-order logic. -/- In Chapter 2 we give an overview of the basic notions of generalized quantifier theory, computability theory, and descriptive complexity theory. -/- In Chapter 3 we prove that PTIME quantifiers are closed under iteration, cumulation and resumption. Next, we discuss the NP-completeness of branching quantifiers. Finally, we show that some Ramsey quantifiers define NP-complete classes of finite models while others stay in PTIME. We also give a sufficient condition for a Ramsey quantifier to be computable in polynomial time. -/- In Chapter 4 we investigate the computational complexity of polyadic lifts expressing various readings of reciprocal sentences with quantified antecedents. We show a dichotomy between these readings: the strong reciprocal reading can create NP-complete constructions, while the weak and the intermediate reciprocal readings do not. Additionally, we argue that this difference should be acknowledged in the Strong Meaning hypothesis. -/- In Chapter 5 we study the definability and complexity of the type-shifting approach to collective quantification in natural language. We show that under reasonable complexity assumptions it is not general enough to cover the semantics of all collective quantifiers in natural language. The type-shifting approach cannot lead outside second-order logic and arguably some collective quantifiers are not expressible in second-order logic. As a result, we argue that algebraic (many-sorted) formalisms dealing with collectivity are more plausible than the type-shifting approach. Moreover, we suggest that some collective quantifiers might not be realized in everyday language due to their high computational complexity. Additionally, we introduce the so-called second-order generalized quantifiers to the study of collective semantics. -/- In Chapter 6 we study the statement known as Hintikka's thesis: that the semantics of sentences like ``Most boys and most girls hate each other'' is not expressible by linear formulae and one needs to use branching quantification. We discuss possible readings of such sentences and come to the conclusion that they are expressible by linear formulae, as opposed to what Hintikka states. Next, we propose empirical evidence confirming our theoretical predictions that these sentences are sometimes interpreted by people as having the conjunctional reading. -/- In Chapter 7 we discuss a computational semantics for monadic quantifiers in natural language. We recall that it can be expressed in terms of finite-state and push-down automata. Then we present and criticize the neurological research building on this model. The discussion leads to a new experimental set-up which provides empirical evidence confirming the complexity predictions of the computational model. We show that the differences in reaction time needed for comprehension of sentences with monadic quantifiers are consistent with the complexity differences predicted by the model. -/- In Chapter 8 we discuss some general open questions and possible directions for future research, e.g., using different measures of complexity, involving game-theory and so on. -/- In general, our research explores, from different perspectives, the advantages of identifying meaning with algorithms and applying computational complexity analysis to semantic issues. It shows the fruitfulness of such an abstract computational approach for linguistics and cognitive science. (shrink)

The formal theory of the Model of Hierarchical Complexity is presented. Complexity theories generally exclude the concept of hierarchical complexity; Developmental Psychology has included it for over 20 years. It also applies to social systems and non-human systems. Formal axioms for the Model are outlined. The model assigns an order of hierarchical complexity to every task, using natural numbers, establishing a quantal notion of stage and stages of performance. This formalizes properties of stage theories in (...) psychology. The formal theory of the model enables extending the concept of hierarchical complexity to any field where tasks and their performances exist. (shrink)

Two assertions of Halford et al. are critiqued: their claim of priority in relational complexity analysis and the sufficiency for cognitive development of their relational-complexity analysis of tasks. Critical discussion of concrete task analyses (i.e., the relational complexity of proportionality problems, of balance scale problems, and the Tower of Hanoi) serves, by way of counterexamples, to highlight problems in their method.

The Model of Hierarchical Complexity is introduced in terms of its main concepts, background, and applications. As a general, quantitative behavioral developmental theory, the Model enables examination of universal patterns of evolution and development. Behavioral tasks are definable and their organization of information in increasingly greater hierarchical, or vertical, complexity is measurable. Fifteen orders of hierarchical complexity account for task performances across domains, ranging from those of machines to creative geniuses. The four most complex orders are (...) demonstrated by postformal stages of thought, which measure beyond formal operations, the highest stage found by Piaget for adults. (shrink)

Relational complexity provides a metric for measuring task demands, and in this respect has much in common with the cognitive complexity and control theory. However, relational complexity does not account for the relative difficulty of different relational types, and appears to underestimate the importance of changes in children's ability to act on the basis of their understanding.

There is something genuinely puzzling about large-scale simplicity emerging in systems that are complex at the small scale. Consider, for example, a population of hares. Clearly, the number of hares at any given time depends on hare fertility rates, the weather, the number of predators, the health of the predators, availability of hare resources, motor vehicle traffic, individual hare locations, colour of individual hares, and so on. Indeed, given the incredibly complexity of the hares’ environment at the small-scale, it (...) is amazing that anything can be said about hare abundances. But not only can we say something about hare abundances, we can formulate equations for hare abundance as a function of time that are remarkably accurate. But most amazing of all is that such equations have very few parameters—in the simplest cases, just the growth rate and an initial population abundance. How can this be? How can we ignore all the small-scale factors when they clearly play major roles in determining abundance? Put somewhat more grandiosely: How is population ecology possible? Of course it’s not just population ecology that exhibits such small-scale complexity and large-scale simplicity. Other important systems include the weather (in which various cyclic behaviours like El Ni˜ nos and ice ages occur despite the day-to-day chaos) and gases in equilibrium (in which apparently random motions of molecules result in the gas obeying the ideal gas law). The examples can easily be multiplied. The general problem is the same: How can seemingly unpredictable and complex microbehaviour of complex systems result in predictable and simple macrobehaviour? Providing an answer to this question is the central task of Michael Strevens’ excellent book Bigger than Chaos: Understanding Complexity through Probability. (shrink)

The task of designing effective economic and political institutions requires substantial foresight. The designer must anticipate not only the behavior of individual actors, but also how that behavior will aggregate. Rising complexity brought about by increases in speeds of adaptation, diversity, connectedness, and interdependence make institutional design all the more challenging. Given the focus on equilibria, the extant literature on mechanism design might appear incapable of coping with this complexity. Yet, I suggest that a deeper engagement with (...) the origins of the mechanism-design framework reveals insights that may help us design robust, adaptive institutions that can harness complexity. (shrink)

Hierarchical complexity's unidimensional measurement can help rectify policy confusion and debates about democratization and terrorism reduction. Stages of political development examined using the method yield task analyses demonstrating why stages cannot be skipped or rushed. Composites of stages and societies' transitions implicate policy change for anti-corruption and nation-building. New indexes for the political domain should be developed using hierarchical complexity to account for and measure a multitude of political tasks regardless of content or context. Measurement offers a (...) reliable, empirical basis to resist attempts to rush development. Hierarchical complexity accounts for why such efforts are doomed in advance to fail. (shrink)

Many proposals for logic-based formalisations of argumentation consider an argument as a pair (Φ,α), where the support Φ is understood as a minimal consistent subset of a given knowledge base which has to entail the claim α. In case the arguments are given in the full language of classical propositional logic reasoning in such frameworks becomes a computationally costly task. For instance, the problem of deciding whether there exists a support for a given claim has been shown to be (...) -complete. In order to better understand the sources of complexity (and to identify tractable fragments), we focus on arguments given over formulæ in which the allowed connectives are taken from certain sets of Boolean functions. We provide a complexity classification for four different decision problems (existence of a support, checking the validity of an argument, relevance and dispensability) with respect to all possible sets of Boolean functions. Moreover, we make use of a general schema to enumerate all arguments to show that certain restricted fragments permit polynomial delay. Finally, we give a classification also in terms of counting complexity. (shrink)

As brightly shown by Mainzer [24], the science of complexity has many distinct origins in many disciplines. Those various origins has led to “an interdisciplinary methodology to explain the emergence of certain macroscopic phenomena via the nonlinear interactions of microscopic elements” (ibid.). This paper suggests that the parallel and strong expansion of modeling and simulation - especially after the Second World War and the subsequent development of computers - is a rationale which also can be counted as an explanation (...) of this emergence. With the benefit of hindsight, one can find three periods in the methodologies of modeling in the empirical sciences: 1st the simple modeling of the simple, 2nd the simple modeling of the complex, 3rd the complex modeling and simulation of the complex. Our main thesis is that the current spreading (since the 90’s) of complex computer simulations of systems of models (where a simulation is no more a step by step calculus of a unique logico-mathematical model) is another promising dimension of the science of complexity. Following this claim, we propose to distinguish three different types of computer simulations in the context of complex systems’ modeling. Finally, we show that these types of simulations lead to three different types of weak emergence, too. (shrink)

Individuals do not operate “at a stage of development.” They operate at a range of different levels of hierarchical complexity depending on skill area, task, context, degree of support, and other variables. It is thus necessary to postulate the concept of domain to refer to the particular conceptual, behavioral, or affective area within which activity operates. The concept raises questions and implications for theory building and application. Such issues are elaborated by discussing a variety of domains and social (...) contexts. A postformal case example of leadership in higher education illuminates the concept of domains and the interrelationships among domains. (shrink)

In a simple economic decision problem with multi-tasking the dimensionality of the problem is neither a necessary nor a sufficient measure of complexity. Rather, dimension is good measure of complexity when there is an aggregate resource constraint that creates an interaction between the different activities, resulting in a problem with high algorithmic complexity.

In modern, Western societies the purpose of schooling is to ensure that school-goers acquire knowledge of pre-existing practices, events, entities and so on. The knowledge that is learned is then tested to see if the learner has acquired a correct or adequate understanding of it. For this reason, it can be argued that schooling is organised around a representational epistemology: one which holds that knowledge is an accurate representation of something that is separate from knowledge itself. Since the object of (...) knowledge is assumed to exist separately from the knowledge itself, this epistemology can also be considered ‘spatial.’ In this paper we show how ideas from complexity have challenged the spatial epistemology’ of representation and we explore possibilities for an alternative ‘temporal’ understanding of knowledge in its relationship to reality. In addition to complexity, our alternative takes its inspiration from Deweyan ‘transactional realism’ and deconstruction. We suggest that ‘knowledge’ and ‘reality’ should not be understood as separate systems which somehow have to be brought into alignment with each other, but that they are part of the same emerging complex system which is never fully ‘present’ in any (discrete) moment in time. This not only introduces the notion of time into our understanding of the relationship between knowledge and reality, but also points to the importance of acknowledging the role of the ‘unrepresentable’ or ‘incalculable’. With this understanding knowledge reaches us not as something we receive but as a response, which brings forth new worlds because it necessarily adds something (which was not present anywhere before it appeared) to what came before. This understanding of knowledge suggests that the acquisition of curricular content should not be considered an end in itself. Rather, curricular content should be used to bring forth that which is incalculable from the perspective of the present. The epistemology of emergence therefore calls for a switch in focus for curricular thinking, away from questions about presentation and representation and towards questions about engagement and response. (shrink)

Complexity and Postmodernism explores the notion of complexity in the light of contemporary perspectives from philosophy and science. The book integrates insights from complexity and computational theory with the philosophical position of thinkers including Derrida and Lyotard. Paul Cilliers takes a critical stance towards the use of the analytical method as a tool to cope with complexity, and he rejects Searle's superficial contribution to the debate.

Introduction to complexity and complex systems -- Introduction to large linear systems -- Introduction to biochemical oscillators and nonlinear biochemical systems -- Modularity, redundancy, degeneracy, pleiotropy and robustness in complex biological systems -- The evolution of biological complexity; invertebrate immune systems -- Irreducible and specified complexity in living systems -- The complex adaptive and innate human immune systems -- Complexity in quasispecies : microRNAs -- Introduction to complexity in economic systems -- Complexity in quasispecies (...) : micrornas -- Dealing with complexity. (shrink)

This book explains the relationship between intelligence and environmental complexity, and in so doing links philosophy of mind to more general issues about the relations between organisms and environments, and to the general pattern of 'externalist' explanations. The author provides a biological approach to the investigation of mind and cognition in nature. In particular he explores the idea that the function of cognition is to enable agents to deal with environmental complexity. The history of the idea in the (...) work of Dewey and Spencer is considered, as is the impact of recent evolutionary theory on our understanding of the place of mind in nature. (shrink)

Arguments about the evolutionary function of phenomenal consciousness are beset by the problem of epiphenomenalism. For if it is not clear whether phenomenal consciousness has a causal role, then it is difficult to begin an argument for the evolutionary role of phenomenal consciousness. We argue that complexity arguments offer a way around this problem. According to evolutionary biology, the structural complexity of a given organ can provide evidence that the organ is an adaptation, even if nothing is known (...) about the causal role of the organ. Evidence from cognitive neuropsychology suggests that phenomenal consciousness is structurally complex in the relevant way, and this provides prima facie evidence that phenomenal consciousness is an adaptation. Furthermore, we argue that the complexity of phenomenal consciousness might also provide clues about the causal role of phenomenal consciousness. (shrink)

Different proofs may be distinguished in terms of complexity. This paper reviews the inefficiency of current logical systems.

It is becoming rather monotonous continually reading articles that tell us how the concept of and the requirements for the modern organization are changing, how these are more complex than ever, and how a paradigm shift is necessary in order to facilitate our continued analysis, and management, of such entities. We are told that we must distribute decision making, encourage individual autonomy, and strive to innovate in the rapidly changing environment that characterizes the apparent New World Order. The list is (...) as far reaching as it is impressive. These concepts coincide with a new, or at least emerging, description of organizations. This “paradigm” appears, from particular presentations at least, wholly to reject the long-held prevailing paradigm of the mechanistic, efficiency-driven, hierarchical, command-and-control organization. (We would question the “whollyness” of this position.) Complexity science has emerged from the field of possible candidates as a prime contender for the top spot in the next era of management science. (shrink)

In three experiments, we investigated the computational complexity of German reciprocal sentences with different quantificational antecedents. Building upon the tractable cognition thesis (van Rooij, 2008) and its application to the verification of quantifiers (Szymanik, 2010) we predicted complexity differences among these sentences. Reciprocals with all-antecedents are expected to preferably receive a strong interpretation (Dalrymple et al., 1998), but reciprocals with proportional or numerical quantifier antecedents should be interpreted weakly. Experiment 1, where participants completed pictures according to their preferred (...) interpretation, provides evidence for these predictions. Experiment 2 was a picture verification task. The results show that the strong interpretation was in fact possible for tractable all but one-reciprocals, but not for exactly n. The last experiment manipulated monotonicity of the quantifier antecedents. (shrink)

In a world of ever growing specialization, the issue of complexity attracts a good amount of attention from cross-disciplinary points of view as this Congress provides evidence. Charles S. Peirce's thought may help us not only to shoulder once again philosophical responsibility which has been largely abdicated by much of 20th century philosophy, but also to tackle some of the most stubborn contemporary problems. The founder of pragmatism identified one century ago most of these problems, and he also mapped (...) out some paths that we could follow to overcome the poverty of contemporary scientistic reductionism. One of these paths is related with the issue of complexity, that lies at the heart of all his conception. -/- Along this line, the aim of my paper is to describe what Peirce can teach about complexity to semioticians coming from very different scientific backgrounds. The lecture will be divided in three sections: 1) a presentation of Peirce, stressing his personal authority as a scientist philosopher, providing also some biographical details; 2) the theory of categories as the heart of complexity according to Peirce and, finally, 3) some consequences of Peirce's notion of complexity in relation with abduction and creativity, semiosis, cross-disciplinarity and communication. -/- . (shrink)

This volume provides an accessible theoretical introduction to the topic of complexity theory while considering its broader implications for educational change.

Participants were required to switch among randomly ordered tasks, and instructional cues were used to indicate which task to execute. In Experiments 1 and 2, the participants indicated their readiness for the task switch before they received the target stimulus; thus, each trial was associated with two primary dependent measures: (1) readiness time and (2) target reaction time. Slow readiness responses and instructions emphasizing high readiness were paradoxically accompanied by slow target reaction time. Moreover, the effect of (...) class='Hi'>task switching on readiness time was an order of magnitude smaller then the (objectively estimated) duration required for task preparation (Experiment 3). The results strongly suggest that participants have little conscious awareness of their preparedness and challenge commonly accepted assumptions concerning the role of consciousness in cognitive control. (shrink)

We study the computational complexity of polyadic quantifiers in natural language. This type of quantification is widely used in formal semantics to model the meaning of multi-quantifier sentences. First, we show that the standard constructions that turn simple determiners into complex quantifiers, namely Boolean operations, iteration, cumulation, and resumption, are tractable. Then, we provide an insight into branching operation yielding intractable natural language multi-quantifier expressions. Next, we focus on a linguistic case study. We use computational complexity results to (...) investigate semantic distinctions between quantified reciprocal sentences. We show a computational dichotomy<br>between different readings of reciprocity. Finally, we go more into philosophical speculation on meaning, ambiguity and computational complexity. In particular, we investigate a possibility to<br>revise the Strong Meaning Hypothesis with complexity aspects to better account for meaning shifts in the domain of multi-quantifier sentences. The paper not only contributes to the field of the formal<br>semantics but also illustrates how the tools of computational complexity theory might be successfully used in linguistics and philosophy with an eye towards cognitive science. (shrink)

What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of individual neurons produce something as extraordinarily complex as consciousness? What is it that guides self-organizing structures like the immune system, the World Wide Web, the global economy, and the human genome? These are just a few of the fascinating and elusive questions that the science of complexity seeks to answer. In this remarkably accessible and companionable book, leading complex (...) systems scientist Melanie Mitchell provides an intimate, detailed tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. Comprehending such systems requires a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries. Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. She explores as well the relationship between complexity and evolution, artificial intelligence, computation, genetics, information processing, and many other fields. Richly illustrated and vividly written, Complexity: A Guided Tour offers a comprehensive and eminently comprehensible overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for the field's contribution to solving some of the most important scientific questions of our time. (shrink)

The problem of computational complexity of semantics for some natural language constructions – considered in [M. Mostowski, D. Wojtyniak 2004] – motivates an interest in complexity of Ramsey quantifiers in finite models. In general a sentence with a Ramsey quantifier R of the following form Rx, yH(x, y) is interpreted as ∃A(A is big relatively to the universe ∧A2 ⊆ H). In the paper cited the problem of the complexity of the Hintikka sentence is reduced to the (...) problem of computational complexity of the Ramsey quantifier for which the phrase “A is big relatively to the universe” is interpreted as containing at least one representative of each equivalence class, for some given equvalence relation. In this work we consider quantifiers Rf, for which “A is big relatively to the universe” means “card(A) > f (n), where n is the size of the universe”. Following [Blass, Gurevich 1986] we call R mighty if Rx, yH(x, y) defines N P – complete class of finite models. Similarly we say that Rf is N P –hard if the corresponding class is N P –hard. We prove the following theorems. (shrink)

We study the computational complexity of reciprocal sentences with quantified antecedents. We observe a computational dichotomy between different interpretations of reciprocity, and shed some light on the status of the so-called Strong Meaning Hypothesis.

The main claim of this paper is that notions of implementation based on an isomorphic correspondence between physical and computational states are not tenable. Rather, ``implementation'' has to be based on the notion of ``bisimulation'' in order to be able to block unwanted implementation results and incorporate intuitions from computational practice. A formal definition of implementation is suggested, which satisfies theoretical and practical requirements and may also be used to make the functionalist notion of ``physical realization'' precise. The upshot of (...) this new definition of implementation is that implementation cannot distinguish isomorphic bisimilar from non-isomporphic bisimilar systems anymore, thus driving a wedge between the notions of causal and computational complexity. While computationalism does not seem to be affected by this result, the consequences for functionalism are not clear and need further investigations. (shrink)

" The Moment of Complexity is a profoundly original work. In remarkable and insightful ways, Mark Taylor traces an entirely new way to view the evolution of our culture, detailing how information theory and the scientific concept of complexity can be used to understand recent developments in the arts and humanities. This book will ultimately be seen as a classic."-John L. Casti, Santa Fe Institute, author of Godel: A Life of Logic, the Mind, and Mathematics The science of (...) complexity accounts for that inscrutable mix of chaos and order that governs our natural world. Complexity explains how networks emerge and function, how species organize into ecosystems, how stars form into galaxies, and how just a few sequences of DNA can account for so many different life forms. Recently, the idea of complexity has taken the worlds of business and politics by storm. The concept is used to account for phenomena as varied as the behavior of the stock market, the response of voting populations, and the effects of risk management. Even Disney has used complexity theory to manage crowd control at its theme parks. Given the startling development of new information technologies, we now live in a moment of unprecedented complexity, an era in which change occurs faster than our ability to comprehend it. With The Moment of Complexity , Mark C. Taylor offers a timely map for this unfamiliar terrain opening in our midst, unfolding an original philosophy through a remarkable synthesis of science and culture. According to Taylor, complexity is not just a breakthrough scientific concept, but the defining quality of the post-Cold War era. The flux of digital currents swirling around us, he argues, has created a new network culture with its own distinctive logic and dynamic. Drawing on resources from information theory and evolutionary biology, Taylor explains the operation of complex adaptive systems in social and cultural processes and captures a whole new zeitgeist in the making. To appreciate the significance of our emerging network culture, he claims, we need not only to understand contemporary scientific and technological transformations, but also to explore the subtle influences of art, architecture, philosophy, religion, and higher education. The Moment of Complexity , then, is a remarkable work of cultural analysis on a scale rarely seen today. To follow its trajectory is to learn how we arrived at this critical moment in our culture, and to know where we might head in the twenty-first century. (shrink)

The aim of this book is to show how supramolecular complexity of cell organization can dramatically alter the functions of individual macromolecules within a cell. The emergence of new functions which appear as a consequence of supramolecular complexity, is explained in terms of physical chemistry. The book is interdisciplinary, at the border between cell biochemistry, physics and physical chemistry. This interdisciplinarity does not result in the use of physical techniques but from the use of physical concepts to study (...) biological problems. In the domain of complexity studies, most works are purely theoretical or based on computer simulation. The present book is partly theoretical, partly experimental and theory is always based on experimental results. Moreover, the book encompasses in a unified manner the dynamic aspects of many different biological fields ranging from dynamics to pattern emergence in a young embryo. The volume puts emphasis on dynamic physical studies of biological events. It also develops, in a unified perspective, this new interdisciplinary approach of various important problems of cell biology and chemistry, ranging from enzyme dynamics to pattern formation during embryo development, thus paving the way to what may become a central issue of future biology. (shrink)

The theme of this book is formed by a pair of concepts: the concept of formal language as carrier of the precise expression of meaning, facts and problems, and the concept of algorithm or calculus, i.e. a formally operating procedure for the solution of precisely described questions and problems. The book is a unified introduction to the modern theory of these concepts, to the way in which they developed first in mathematical logic and computability theory and later in automata theory, (...) and to the theory of formal languages and complexity theory. Apart from considering the fundamental themes and classical aspects of these areas, the subject matter has been selected to give priority throughout to the new aspects of traditional questions, results and methods which have developed from the needs or knowledge of computer science and particularly of complexity theory. It is both a textbook for introductory courses in the above-mentioned disciplines as well as a monograph in which further results of new research are systematically presented and where an attempt is made to make explicit the connections and analogies between a variety of concepts and constructions. (shrink)

One new tradition that has emerged from early research on autonomous robots is embodied cognitive science. This paper describes the relationship between embodied cognitive science and a related tradition, synthetic psychology. It is argued that while both are synthetic, embodied cognitive science is antirepresentational while synthetic psychology still appeals to representations. It is further argued that modern connectionism offers a medium for conducting synthetic psychology, provided that researchers analyze the internal representations that their networks develop. The paper then provides a (...) detailed example of the synthetic approach by showing how the construction (and subsequent analysis) of a connectionist network can be used to contribute to a theory of how humans solve Piaget's classic balance scale task. (shrink)

Mental state reasoning or theory-of-mind has been the subject of a rich body of imaging research. Although such investigations routinely tap a common set of regions, the precise function of each area remains a contentious matter. With the help of functional magnetic resonance imaging (fMRI), we sought to determine which areas are involved when processing mental state or intentional metarepresentations by focusing on the relational aspect of such representations. Using non-intentional relational representations such as spatial relations between persons and between (...) objects as a contrast, the results ascertained the involvement of the precuneus, the temporal poles, and the medial prefrontal cortex in the processing of intentional representations. In contrast, the anterior superior temporal sulcus and the left temporo-parietal junction were implicated when processing representations that refer to the presence of persons in relational contexts in general. The right temporo-parietal junction, however, was specifically activated for persons entering spatial relations. The level of representational complexity, a previously unexplored factor, was also found to modulate the neural response in some brain regions, such as the medial prefrontal cortex and the right temporo-parietal junction. These findings highlight the need to take into account the critical roles played by an extensive network of neural regions during mental state reasoning. (shrink)

We observe that the classification problem for countable models of arithmetic is Borel complete. On the other hand, the classification problems for finitely generated models of arithmetic and for recursively saturated models of arithmetic are Borel; we investigate the precise complexity of each of these. Finally, we show that the classification problem for pairs of recursively saturated models and for automorphisms of a fixed recursively saturated model are Borel complete.

Linguistic dependencies between non-adjacent words have been shown to cause comprehension difficulty, compared with local dependencies. According to one class of sentence comprehension accounts, non-local dependencies are difficult because they require the retrieval of the first dependent from memory when the second dependent is encountered. According to these memory-based accounts, making the first dependent accessible at the time when the second dependent is encountered should help alleviate the difficulty associated with the processing of non-local dependencies. In a dual-task paradigm, (...) participants read sentences that did or did not contain a non-local dependency (i.e., object- and subject-extracted cleft constructions) while simultaneously remembering a word. The memory task was aimed at making the word held in memory accessible throughout the sentence. In an object-extracted cleft (e.g., It was Ellen whom John consulted…), the object (Ellen) must be retrieved from memory when consulted is encountered. In the critical manipulation, the memory word was identical to the verb's object (ELLEN). In these conditions, the extraction effect was reduced in the comprehension accuracy data and eliminated in the reading time data. These results add to the body of evidence supporting memory-based accounts of syntactic complexity. (shrink)

The SAGE Handbook of Complexity and Management will be the first substantive scholarly work to provide a map of the state of art research in the growing field ...

Book review of Bechtel and Richardson, Discovering Complexity (1993). Review suggests that one theme of the book -- that scientific reason is "constituted" in part by a cognitive strategy of finding complexity -- is not fully supported.

Learning theory has frequently been applied to language acquisition, but discussion has largely focused on information theoretic problems—in particular on the absence of direct negative evidence. Such arguments typically neglect the probabilistic nature of cognition and learning in general. We argue first that these arguments, and analyses based on them, suffer from a major flaw: they systematically conflate the hypothesis class and the learnable concept class. As a result, they do not allow one to draw significant conclusions about the learner. (...) Second, we claim that the real problem for language learning is the computational complexity of constructing a hypothesis from input data. Studying this problem allows for a more direct approach to the object of study—the language acquisition device—rather than the learnable class of languages, which is epiphenomenal and possibly hard to characterize. The learnability results informed by complexity studies are much more insightful. They strongly suggest that target grammars need to be objective, in the sense that the primitive elements of these grammars are based on objectively definable properties of the language itself. These considerations support the view that language acquisition proceeds primarily through data-driven learning of some form. (shrink)

Self-organized complexity in the physical, biological, and social sciences Donald L Turcotte*f and John B. Rundle* *Department of Earth and Atmospheric ...

Introduction -- Elucidating complexity theories -- Complexity in the natural sciences -- Complexity in social theory -- Towards transdisciplinarity -- Complexity in philosophy: complexification and the limits to knowledge -- Complexity in ethics -- Earth in the anthropocene -- Complexity and climate change -- American dreams, ecological nightmares and new visions -- Complexity and sustainability: wicked problems, gordian knots and synergistic solutions -- Conclusion.

This book presents an up-to-date, unified treatment of research in bounded arithmetic and complexity of propositional logic, with emphasis on independence proofs and lower bound proofs. The author discusses the deep connections between logic and complexity theory and lists a number of intriguing open problems. An introduction to the basics of logic and complexity theory is followed by discussion of important results in propositional proof systems and systems of bounded arithmetic. More advanced topics are then treated, including (...) polynomial simulations and conservativity results, various witnessing theorems, the translation of bounded formulas (and their proofs) into propositional ones, the method of random partial restrictions and its applications, direct independence proofs, complete systems of partial relations, lower bounds to the size of constant-depth propositional proofs, the method of Boolean valuations, the issue of hard tautologies and optimal proof systems, combinatorics and complexity theory within bounded arithmetic, and relations to complexity issues of predicate calculus. Students and researchers in mathematical logic and complexity theory will find this comprehensive treatment an excellent guide to this expanding interdisciplinary area. (shrink)

Introduction -- The legal aspects -- Corporate governance and corporate performance -- Complexity and corporate governance -- Conclusion.

This is a comprehensive discussion of complexity as it arises in physical, chemical, and biological systems, as well as in mathematical models of nature. Common features of these apparently unrelated fields are emphasised and incorporated into a uniform mathematical description, with the support of a large number of detailed examples and illustrations. The quantitative study of complexity is a rapidly developing subject with special impact in the fields of physics, mathematics, information science, and biology. Because of the variety (...) of the approaches, no comprehensive discussion has previously been attempted. This book will be of interest to graduate students and researchers in physics (nonlinear dynamics, fluid dynamics, solid-state, cellular automata, stochastic processes, statistical mechanics and thermodynamics), mathematics (dynamical systems, ergodic and probability theory), information and computer science (coding, information theory and algorithmic complexity), electrical engineering and theoretical biology. (shrink)

JPVA Journal of Philosophy and the Visual Arts No 6 Complexity Architecture / Art / Philosophy 'Beginning with complexity will involve working with the recognition that there has always been more than one. Here however this insistent "more than one" will be positioned beyond the scope of semantics; rather than complexity occurring within the range of meaning and taking the form of a generalised polysemy, it will be linked to the nature of the object and to its (...) production. Complexity, therefore, will be inextricably connected to the ontology of the object. What this means is that complexity, in resisting the hold of a semantic idealism on the one hand, and the attempt to give to it the position of being the basis of a new foundationalism on the other, becomes a way of thinking both the presence and the production of objects.' Andrew Benjamin The Journal of Philosophy and the Visual Arts has set new standards in its exploration of themes central to philosophy's relation to the visual arts, illuminating areas of art criticism, architecture, feminism as well as philosophy itself. Rather than simply reflecting current trends it provides a forum in which the real developments in the analysis of the visual arts and its larger cultural and political context can be presented. Articles by well known philosophers and theorists, as well as some lesser known, together with writings by artists and architects allow a strong interdisciplinary approach reflecting the Journal's roots in post-structural theory. Previous issues include: Philosophy & the Visual Arts (No 1) Philosophy & Architecture (No 2) Architecture, Space, Painting (No 3) The Body (No 4) Abstraction (No 5). (shrink)

We assessed the automaticity of spatial-numerical and spatial-musical associations by testing their intentionality and load sensitivity in a dual-task paradigm. In separate sessions, 16 healthy adults performed magnitude and pitch comparisons on sung numbers with variable pitch. Stimuli and response alternatives were identical, but the relevant stimulus attribute (pitch or number) differed between tasks. Concomitant tasks required retention of either color or location information. Results show that spatial associations of both magnitude and pitch are load sensitive and that the (...) spatial association for pitch is more powerful than that for magnitude. These findings argue against the automaticity of spatial mappings in either stimulus dimension. (shrink)

Richard Dawkins has popularized an argument which, according to him, proves that there is almost certainly no God. It rests on the assumption that complex and statistically improbable things are more difficult to explain than those that are not, and that any explanatory mechanism that is called on to do the explaining must show how this complexity can be built up from simpler means as it would be useless otherwise. In this paper, I first question what justifies the consideration (...) of the designer’s own complexity. I suggest a different understanding of both order and simplicity inevitable when one considers the psychological counterpart of information. I then assess what seems to be the inference engine of the proposal, the metaphor of biological organisms as either self-programmed machines or algorithms. I show how self-generated organized complexity would not sit well with our knowledge of both abduction and the theorems of information theory applied to genetics. I then turn to the positive side of Dawkins’ challenge, and I review some philosophers and their proposals for how the complexity of the world could be controlled from outside if one wanted to uphold a traditional understanding of God’s simplicity. (shrink)

The paper analyzes the sacred foundations of Western institutional order, moving from an epistemological, historical and legal–aesthetic perspective. Firstly, it identifies an epistemological theory of complexity which, pursuing Hayek’s theory of complexity, Robilant’s notion of informative–normative systems, Popper’s theory of the Worlds, and Dupuy’s theory of endogenous fixed point, will conclusively lead to presenting the hypothesis of World 0 as the World of the foundation of legal thinking, the home of the sacred and the aesthetic. Secondly, it identifies (...) the axiological character of the legal aesthetic as a discipline, a topic that will be taken up in relation to the work of the French historian of canonical law and psychoanalyst Legendre, starting from the analysis of a legal/historiographical context (Corpus Iuris Civilis, Corpus Iuris Canonici, Hobbesian Leviathan, Kelsenian Grundnorm). Thirdly, following Ellul’s thought on secularization, the idea that we now live in a secularized, lay society, lacking in the sacred is revealed as a sort of illusion, the creation of a myth of modernity, only apparently rational. Finally the paper proposes as the task of legal theory the identification of the system of “nomograms” in which the normative message is organized, according to a nonreductionistic approach that forces legal theory to recognize the plurality of the iconic forms of the normative message. The “nomograms” respond to the need of extending the field of legal science to phenomena that the positivist theory of law does not consider important, but which the process of evolution of contemporary society imposes. (shrink)

What exactly is complexity science? Two's company, three is complexity ; Disorder rules, OK? ; Chaos and all that jazz ; Mob mentality ; Getting connected -- What can complexity science do for me? Forecasting financial markets ; Tackling traffic networks and climbing the corporate ladder ; Looking for Mr./Mrs. Right ; Coping with conflict : next-generation wars and global terrorism -- Catching a cold, avoiding super-flu and curing cancer ; The mother of all complexities : our (...) nanoscale quantum world ; To infinity and beyond. (shrink)

We study the computational complexity of the model checking problem for quantifier-free dependence logic ${(\mathcal{D})}$ formulas. We characterize three thresholds in the complexity: logarithmic space (LOGSPACE), non-deterministic logarithmic space (NL) and non-deterministic polynomial time (NP).

Machine generated contents note: -- Miracles and Nasty Surprises -- The Failure of Models & Labels; the Success of Experience & Emergence -- Two Kinds of Coherence - Ascribed and Emergent -- Models, Homologies & Simulacra -- The Ascribed Coherence of Thagard and Weick -- Coherence and Business Success -- Emergence, Coherence & Narrative -- Affordances and Organization -- Homology: Sense-Making revisited -- But Experience is Different -- Complexity tools: the Semiotic Square & Homology -- Steps to Implementation.

Modal dependence logic was introduced recently by Väänänen. It enhances the basic modal language by an operator = (). For propositional variables p 1, . . . , p n , = (p 1, . . . , p n-1, p n ) intuitively states that the value of p n is determined by those of p 1, . . . , p n-1. Sevenster (J. Logic and Computation, 2009) showed that satisfiability for modal dependence logic is complete for nondeterministic (...) exponential time.In this paper we consider fragments of modal dependence logic obtained by restricting the set of allowed propositional connectives. We show that satisfiability for poor man’s dependence logic, the language consisting of formulas built from literals and dependence atoms using ${\wedge, \square, \lozenge}$ (i. e., disallowing disjunction), remains NEXPTIME-complete. If we only allow monotone formulas (without negation, but with disjunction), the complexity drops to PSPACE-completeness.We also extend Väänänen’s language by allowing classical disjunction besides dependence disjunction and show that the satisfiability problem remains NEXPTIME-complete. If we then disallow both negation and dependence disjunction, satisfiability is complete for the second level of the polynomial hierarchy. Additionally we consider the restriction of modal dependence logic where the length of each single dependence atom is bounded by a number that is fixed for the whole logic. We show that the satisfiability problem for this bounded arity dependence logic is PSPACE-complete and that the complexity drops to the third level of the polynomial hierarchy if we then disallow disjunction.In this way we completely classify the computational complexity of the satisfiability problem for all restrictions of propositional and dependence operators considered by Väänänen and Sevenster. (shrink)

In this article I present an alternative philosophy of science based on ideas drawn from the study of complex adaptive systems. As a result of the spectacular expansion in scientific disciplines, the number of scientists and scientific institutions in the twentieth century, I believe science can be characterised as a complex system. I want to interpret the processes of science through which scientists themselves determine what counts as good science. This characterisation of science as a complex system can give an (...) answer to the question why the sciences are so successful in solving growing numbers of problems and correcting their own mistakes. I utilise components of complexity theory to explain and interpret science as a complex system. I first explain the concept of complexity in ordinary language. The explanation of science as a complex system starts with a definition of the basic rules that guide the behaviour of science as a complex system. Next, I show how various sciences result through the implementation of these rules in the study of a specific aspect of reality. The explanation of the growth of science through evolutionary adaptation and learning forms the core of the article. (shrink)

v. 1. Origins of order-creation science : complexity science from basic disciplines -- v. 2. Self-organization, emergence and self-organized criticality -- v. 3. Organization and management complexity dynamics -- v. 4. Agent-based socio-economic simulation -- v. 5. Power-law distributions in society and business.

Psychoneural reduction is under attack again, only this time from a former ally: cognitive neuroscience. It has become popular to think of the brain as a complex system whose theoretically important properties emerge from dynamic, non-linear interactions between its component parts. ``Emergence'' is supposed to replace reduction: the latter is thought to be incapable of explaining the brain qua complex system. Rather than engage this issue at the level of theories of reduction versus theories of emergence, I here emphasize a (...) role that reductionism plays – and will continue to play – even if neuroscience adopts this ``complex systems'' view. In detailed investigations into the function of complex neural circuits, certain questions can only be addressed by moving down levels and scales. This role for reduction also finds a place for approaches that dominate mainstream neuroscience, like the widespread use of experimental techniques and theories from molecular biology and biochemistry. These are difficult to reconcile with the anti-reductionist sentiments of the ``complex systems'' branch of cognitive neuroscience. (shrink)

Recent work in biology and cognitive science depicts a variety of target phenomena as the products of a tangled web of causal influences. Such influences may include both internal and external factors as well as complex patterns of reciprocal causal interaction. Such twisted tales are sometimes seen as a threat to explanatory strategies that invoke notions such as inner programs, genes for and sometimes even internal representations. But the threat, I shall argue, is more apparent than real. Complex causal influence, (...) in and of itself, provides no good reason to reject these familiar explanatory notions. To believe otherwise, I suggest, is generally to commit (at least) one of two seductive errors. The first error is to think that the general notion of a state x coding for an outcome y involves the state's constituting a full description of y. This is what I call the myth of the self-contained code. The second error is to think that the practice of treating certain factors as special (e.g., seeing genes as coding for outcomes in a way environmental factors do not) depends on the (often mistaken) belief that the singled out factor is somehow doing the most real work. Where the amounts of causal influence are evenly spread, it is assumed there can be no reason to treat one factor in a special way. This is what I term the Myth of Explanatory Equality. Avoiding these errors involves reminding ourselves of (1) the rich context-dependence of even standard, unproblematic uses of the notions of code, program and information content (all three make sense only relative to an assumed ecological backdrop) and (2) the difference between explaining why an event occurred and displaying the full workings of a complex causal system. (shrink)

Perceptual tasks such as object matching, mammogram interpretation, mental rotation, and satellite imagery change detection often require the assignment of correspondences to fuse information across views. We apply techniques developed for machine translation to the gaze data recorded from a complex perceptual matching task modeled after fingerprint examinations. The gaze data provide temporal sequences that the machine translation algorithm uses to estimate the subjects' assumptions of corresponding regions. Our results show that experts and novices have similar surface behavior, such (...) as the number of fixations made or the duration of fixations. However, the approach applied to data from experts is able to identify more corresponding areas between two prints. The fixations that are associated with clusters that map with high probability to corresponding locations on the other print are likely to have greater utility in a visual matching task. These techniques address a fundamental problem in eye tracking research with perceptual matching tasks: Given that the eyes always point somewhere, which fixations are the most informative and therefore are likely to be relevant for the comparison task? (shrink)

Current conceptions of the nature of human reasoning make it no longer tenable to assess children's inference by reference to the norms of logical inference. Alternatively, the complexity of the mental models employed in children's inferences can be analysed. This approach is applied to transitive inference, class inclusion, categorical induction, theory of mind, oddity, categorical syllogisms, analogy, and reasoning deficits. It is argued that a coherent account of children's reasoning emerges in that there is correspondence between tasks at the (...) same level of complexity across different domains, and that the inferences of younger children, while impressive and important, are consistently simpler than those of older children. (shrink)

In Unsimple Truths, Sandra Mitchell argues that the long-standing scientific and philosophical deference to reductive explanations founded on simple universal ...

One of the main themes that has emerged from behavioral decision research during the past three decades is the view that people's preferences are often constructed in the process of elicitation. This idea is derived from studies demonstrating that normatively equivalent methods of elicitation (e.g., choice and pricing) give rise to systematically different responses. These preference reversals violate the principle of procedure invariance that is fundamental to all theories of rational choice. If different elicitation procedures produce different orderings of options, (...) how can preferences be defined and in what sense do they exist? This book shows not only the historical roots of preference construction but also the blossoming of the concept within psychology, law, marketing, philosophy, environmental policy, and economics. Decision making is now understood to be a highly contingent form of information processing, sensitive to task complexity, time pressure, response mode, framing, reference points, and other contextual factors. (shrink)

Organizations continue to show renewed focus on managing their ethics programs by developing organizational infrastructures to support their ethics implementation efforts. An important part of this process has been the creation of an ethics officer position. Whether individuals appointed to the position are successful in the role or not may depend on a number of factors. This study presents a suggested framework for their effectiveness. The framework includes a focus on personal, organizational and situational factors to predict performance in the (...) role. The study examines the complex nature of the role. These include task complexity, low task visibility, role conflict, and role ambiguity. Personal, organizational and situational factors that can serve as buffers against the complexities associated with the role are presented. The study suggests that individuals with certain competencies and orientations may be better suitable for the ethics position, and firms need to consider key organizational and situational issues critical to the performance of an ethics officer. The research and practice implications of the study are given. (shrink)

This paper uses recent research in developmental psychology regarding the acquisition of the concept of belief in young children to explore the contrast between a disposition-based account of the principles underlying linguistic communication and the representative and highly influential intention-based accounts of assertional practice advanced by David Lewis and Donald Davidson. Indeed, evidence from recent work in developmental psychology would seem to suggest that disposition-based accounts are not only possible accounts of the acquisition of competence in assertional practice, but are (...) in fact better than their rivals in explaining the way such competence is actually acquired. (shrink)

This book asks not only how the study of white-collar crime can enrich our understanding of crime and justice more generally, but also how criminological ...

Even beginners and young graduate students will have something to learn from this book." (Andre Hautot, Physicalia, Vol. 57 (3), 2005)"All-in-all, this highly ...

Evolution means different things at different stages of development. Higher stage explanations for it are downward assimilated at lower stages. Different scientific explanations for evolution also reflect different stages of development. Hierarchical complexity of tasks in evolution is a behavioral analytic explanation. It is selection processes of various kinds in tandem with changes in selection tasks' orders of hierarchical complexity. There is neither teleology nor evolutionary favoring of the highest stages of performance. Selection tasks at higher orders of (...) complexity increasingly decenter at all scales of behaviors from thought to history's social periods. These processes account for sociopolitical conflicts over evolution. (shrink)

Extended Abstract This book introduces and develops a new, universal method of the scientific comprehension of reality providing the objective, ...

(2) Vol., Classification of Propositional Provability Logics LD Beklemishev Introduction Overview. The idea of an axiomatic approach to the study of ...

The challenges posed by chronic illness have pointed out to epidemiologists the multifactorial complex nature of disease causality. This notion has been referred to as a web of causality. This web extends theoretically beyond risk markers. It includes determinants of emergence/non-emergence of disease. This web of determinants is a form of complex system. Due to its complexity, the determinants within such system are not linked to each others in a linear, predictable manner only. Predictability is possible only on a (...) short-term basis, and unpredictability sets in over the long run. Understanding such a system of determinants calls for articulation and testing of complex models which synthesize our knowledge of multiple determinants at many scales, both biological and otherwise. Given the complexity of this web and existing knowledge about the nonlinearity of such systems, the following question is posed: Can the challenge of studying causality be adequately addressed if emphasis continues to be placed on using tools and methods that are geared towards looking at such system from a linear paradigm? Or is it time to add to the epidemiologic research agenda the notion of nonlinearity and its relevant form of analytical approaches that are being tested in other disciplines? Furthermore, the question posed here applies as well to the study of determinants of health. Addressing determinants of heath adds further complexity to our task. (shrink)

Halford et al.'s analysis of relational complexity provides a possible framework for characterizing the symbolic functions of the prefrontal cortex. Studies of prefrontal patients have revealed that their performance is selectively impaired on tasks that require integration of two binary relations (i.e., tasks that Halford et al.'s analysis would identify as three-dimensional). Analyses of relational complexity show promise of helping to understand the neural substrate of thinking.

The missing ingredients in efforts to develop neural networks and artificial intelligence (AI) that can emulate human intelligence have been the evolutionary processes of performing tasks at increased orders of hierarchical complexity. Stacked neural networks based on the Model of Hierarchical Complexity could emulate evolution's actual learning processes and behavioral reinforcement. Theoretically, this should result in stability and reduce certain programming demands. The eventual success of such methods begs questions of humans' survival in the face of androids of (...) superior intelligence and physical composition. These raise future moral questions worthy of speculation. (shrink)

Three- to six-year-olds were given Heyes's proposed task and theory of mind tasks. Although they correlated, Heyes's was harder; only 50% of participants with a theory of mind reached a criterion of 75% correct. Because of the complex series of inferences involved in Heyes's task, it is possible that one could have a theory of mind and fail Heyes's version.

PART ONE The Evolutionary Metaphors in the Reconstruction of Economics The indiscriminate application of the term 'evolution' however, has led to some ...

Almost before the mourning, the search for the explanation begins. When a public disaster like Saturday's space shuttle crash takes place, it's our natural impulse to find out why - an impulse motivated largely by a desire to avoid such tragedies in the future and to learn from our mistakes. Was it tiles damaged at takeoff? The wrong angle at rollover? A fuel leak? Insufficient funding?

This paper introduces a concept called task muddiness as a metric for higher intelligence. Task muddiness is meant to be inclusive and expendable in nature. The intelligence required to execute a task is measured by the composite muddiness of the task described by multiple muddiness factors. The composite muddiness explains why many challenging tasks are muddy and why autonomous mental development is necessary for muddy tasks. It facilitates better understanding of intelligence, what the human adult mind (...) can do, and how to build a machine to acquire higher intelligence. The task-muddiness indicates a major reason why a higher biological mind is autonomously developed from autonomous, simple-to-complex experience. The paper also discusses some key concepts that are necessary for understanding the mind and intelligence, such as intelligence metrics, the mode a task is conveyed to the task executor, a human and a machine being a joint task performer in the traditional artificial intelligence (AI), a developmental agent (human or machine) being a sole task performer, and the need for autonomy in task-nonexplicit learning. (shrink)

This paper continues the study of the metric topology on $2^{\mathbb {N}}$ that was introduced by S. Binns. This topology is induced by a directional metric where the distance from $Y\in2^{\mathbb {N}}$ to $X\in2^{\mathbb {N}}$ is given by \[\limsup_{n}\frac{C(X\upharpoonright n|Y\upharpoonright n)}{n}.\] This definition is closely related to the notions of effective Hausdorff and packing dimensions. Here we establish that this is a path-connected topology on $2^{\mathbb {N}}$ and that under it the functions $X\mapsto\operatorname{dim}_{\mathcal{H}}X$ and $X\mapsto\operatorname{dim}_{p}X$ are continuous. We also investigate (...) the scalar multiplication operation that was introduced by Binns. The multiplication of a real $X\in2^{\mathbb {N}}$ by an element $\alpha\in[0,1]$ represents a dilution of the information in $X$ by a factor of $\alpha$ . Our main result is to show that every regular real is the dilution of a real of Hausdorff dimension 1. That is, that the information in every regular real can be maximally compressed. (shrink)

Like the Theory of Event Coding (TEC), theories of executive functions depict cognition as a flexible and goal-directed system rather than a reflex-like one. Research on task-switching, a dominant paradigm in executive control, has revealed complex and some apparently counterintuitive results. Many of these are readily explained by assuming, like TEC, that cognitive control is based on selecting information from commensurate representations of stimuli and actions.

Slobodkin proposes that the best intellectual work is done as if it were a game on a simplified playing field.

An important distinction between phonology and syntax has been overlooked. All phonological patterns belong to the regular region of the Chomsky Hierarchy, but not all syntactic patterns do. We argue that the hypothesis that humans employ distinct learning mechanisms for phonology and syntax currently offers the best explanation for this difference.

For various domains in proportional reasoning cognitive development is characterized as a progression through a series of increasingly complex rules. A multiplicative relationship between two task features, such as weight and distance information of blocks placed at both sides of the fulcrum of a balance scale, appears difficult to discover. During development, children change their beliefs about the balance scale several times: from a focus on the weight dimension (Rule I) to occasionally considering the distance dimension (Rule II), guessing (...) (Rule III), and applying multiplication (Rule IV; Siegler, 1981). Because of the detailed empirical findings the balance scale task has become a benchmark task for computational models of proportional reasoning. In this article, we present a large empirical study (N = 420) of which the findings provide a challenge for computational models. The effect of feedback and the effect of individually adapted training items on rule transition were tested for children using Rule I or Rule II. Presenting adapted training items initiates belief revision for Rule I but not for Rule II. The experience of making mistakes (by providing feedback) induces a change for both Rule I and Rule II. However, a delayed posttest shows that these changes are preserved after 2 weeks only for children using Rule I. We conclude that the transition from Rule I to Rule II differs from the transition from Rule II to a more complex rule. Concerning these empirical findings, we will review performance of computational models and the implications for a future belief revision model. It is one Thing, to show a Man that he is in an Error, and another, to put him in possession of Truth. John Locke. (shrink)

Complex problem solving is often an integration of perceptual processing and deliberate planning. But what balances these two processes, and how do novices differ from experts? We investigate the interplay between these two in the game of SET. This article investigates how people combine bottom-up visual processes and top-down planning to succeed in this game. Using combinatorial and mixed-effect regression analysis of eye-movement protocols and a cognitive model of a human player, we show that SET players deploy both bottom-up and (...) top-down processes in parallel to accomplish the same task. The combination of competition and cooperation of both types of processes is a major factor of success in the game. Finally, we explore strategies players use during the game. Our findings suggest that within-trial strategy shifts can occur without the need of explicit meta-cognitive control, but rather implicitly as a result of evolving memory activations. (shrink)

Stanovich & West's dual-system represents a major development in an understanding of reasoning and rationality. Their notion of System 1 functioning as a computational escape hatch during the processing of complex tasks may deserve a more central role in explanations of reasoning performance. We describe examples of apparent escape-hatch processing from the reasoning and judgement literature.