Based on an endorsement of the hypothesis of extended cognition , this paper proposes a criticism of the representationalist assumptions that still pertain to these contemporary models of cognition. I first rehearse some basic problems akin to any representationalist model of cognition, before proposing some more specific arguments directed against the necessity, the plausibility, and the coherence of the marriage between extended cognition and contemporary representationalism . Extended and distributed models of cognition have the resources to get rid of (...) representationalism, and they should better do it. Their adherence to representationalism might be an by-product of the extended character of the scientific study of cognition. (shrink)

Based on an endorsement of the hypothesis of extended cognition, this paper proposes a criticism of the representationalist assumptions that still pertain to these contemporary models of cognition. I first rehearse some basic problems akin to any representationalist model of cognition, before proposing some more specific arguments directed against the necessity, the plausibility, and the coherence of the marriage between extended cognition and contemporary representationalism. Extended and distributed models of cognition have the resources to get rid of representationalism, and (...) they should better do it. Their adherence to representationalism might be an by-product of the extended character of the scientific study of cognition. (shrink)

Resource Bounded Agents Resource bounded agents are persons who have information processing limitations. All persons and other cognitive agents who have bodies are such that their sensory transducers have limited resolution and discriminatory ability; their information processing speed and power is bounded by some threshold; and their memory and … Continue reading Resource Bounded Agents →.

In this paper I draw from Martin Heidegger’s phenomenology of the 1920s to outline some basic features of his theory of intentionality that I believe have not been fully appreciated or utilized, and that allow for both novel and fruitful interventions in questions about meaning, the relationship between mind and the world, and epistemic justification, principally as they appear in John McDowell’s synoptic project in Mind and World. I argue that while elements of McDowell’s picture are ultimately unsatisfying and problematic, (...) much of his conceptual framework can and should be put into dialogue with Heidegger’s, and that in so doing we make available powerful resources for amending the McDowellian account. Moreover, these emendations have attractive implications for his distinctive desiderata. In particular, they provide original conceptions of normativity’s place in nature, of the boundaries of the space of reasons, and of the relationship between the answerability of thought both to the world and to human beings as a rational community. (shrink)

There have been two major lines of research aimed at capturing resource-bounded players in game theory. The first, initiated by Rubinstein (), charges an agent for doing costly computation; the second, initiated by Neyman (), does not charge for computation, but limits the computation that agents can do, typically by modeling agents as finite automata. We review recent work on applying both approaches in the context of decision theory. For the first approach, we take the objects of choice in (...) a decision problem to be Turing machines, and charge players for the “complexity” of the Turing machine chosen (e.g., its running time). This approach can be used to explain well-known phenomena like first-impression-matters biases (i.e., people tend to put more weight on evidence they hear early on) and belief polarization (two people with different prior beliefs, hearing the same evidence, can end up with diametrically opposed conclusions) as the outcomes of quite rational decisions. For the second approach, we model people as finite automata, and provide a simple algorithm that, on a problem that captures a number of settings of interest, provably performs optimally as the number of states in the automaton increases. (shrink)

The objective of this paper is to construct an implementable theory of rational decision-making for cognitive agents subject to realistic resource constraints. It is argued that decision-making should select actions indirectly by selecting plans that prescribe them. It is also argued that although expected values provide the tool for evaluating plans, plans cannot be compared straightforwardly in terms of their expected values, and the objective of a realistic agent cannot be to find optimal plans. The theory of Locally Global (...) planning is proposed as a realistic alternative to standard "maximizing" theories of rational decision-making. (shrink)

What is the role of attention in the dialectics of memory and communication? How far is attention functioning as a medium? Which role does attention play in the information management practices? Attention is not only fundamental to human existence but also to the process of understanding. If understanding is mediated by memory and communication then attention can be identified with the medium. So whenever you search to explain the role and mechanisms of memory in the information society, the question of (...) attention is asked immediately. Furthermore, attention can be analyzed under the following topics: as cognitive process, as subjective, intersubjective and cultural phenomenon, and as resource and medium within an 'Attention Economy'. Whereas the first aspect has to be seen in the context of empirical studies in psychology and cognitive sciences, the phenomenological, cultural, and economic aspects seem to have common points and similar implications in their theoretical approaches. In the last twenty years, the notion of attention has been the central core of several discourses in German phenomenology, economy and cultural studies. Similar to Georg Franck's theory of mental capitalism, the idea of an attention economy also was followed up in the American discourse. This article is supposed to explore the role of attention and its function as a medium within communication, cultural memory and science. (shrink)

Previous theory and research on bounded rationality has emphasized how limited cognitive resources constrain people from making utility maximizing choices. This paper expands the concept of bounded rationality to consider how people’s rationality may be constrained by their internalization of a qualitatively distinct standard for sound judgment, which is commonly labeled reasonableness. In contrast to rationality, the standard of reasonableness provides guidance for making choices in situations that involve balancing incommensurable values and interests or reconciling conflicting (...) points-of-view. We review recent evidence showing that laypeople readily recognize the distinctions between rationality and reasonableness and thus are able to utilize these as distinct standards to inform their everyday decision-making. The fact that people appear to have internalized rationality and reasonableness as distinct standards of sound judgment supports the notion that people’s pursuit of rationality may be bounded by their determination to also be reasonable. (shrink)

Theories of rational decision making often abstract away from computational and other resource limitations faced by real agents. An alternative approach known as resource rationality puts such matters front and center, grounding choice and decision in the rational use of finite resources. Anticipated by earlier work in economics and in computer science, this approach has recently seen rapid development and application in the cognitive sciences. Here, the theory of rationality plays a dual role, both as a framework for (...) normative assessment and as a source of scientific hypotheses about how mental processes in fact work. The latter project, often called rational analysis, depends for its success on a fine-grained characterization of the computational problem facing a decision maker, which may in turn depend on realistic assumptions about what the relevant agent is like. As a consequence, resource rationality involves a delicate, but often fruitful interplay between the normative and the descriptive. (shrink)

All forms of cognition, whether natural or artificial, are subject to constraints of their computing architecture. This assumption forms the tenet of virtually all general theories of cognition, including those deriving from bounded optimality and bounded rationality. In this letter, we highlight an unresolved puzzle related to this premise: what are these constraints, and why are cognitive architectures subject to cognitive constraints in the first place? First, we lay out some pieces along the puzzle edge, such (...) as computational tradeoffs inherent to neural architectures that give rise to rational bounds of cognition. We then outline critical next steps for characterizing cognitive bounds, proposing that some of these bounds can be subject to modification by cognition and, as such, are part of what is being optimized when cognitive agents decide how to allocate cognitive resources. We conclude that these emerging views may contribute to a more holistic perspective on the nature of cognitive bounds, as well as their alteration subject to cognition. (shrink)

An agent-centered, goal-directed, resource-bound logic of human reasoning would do well to note that individual cognitive agency is typified by the comparative scantness of available cognitive resources—information, time, and computational capacity, to name just three. This motivates individual agents to set their cognitive agendas proportionately, that is, in ways that carry some prospect of success with the resources on which they are able to draw. It also puts a premium on cognitive strategies which make (...) economical use of those resources. These latter I callscant-resource adjustment strategies,and they supply the context for an analysis of abduction. The analysis is Peircian in tone, especially in the emphasis it places on abduction’signorance-preservingcharacter. My principal purpose here is to tie abduction’s scarce-resource adjustment capacity to its ignorance preservation. (shrink)

Topics in Cognitive Science, Volume 14, Issue 3, Page 528-549, July 2022.

Bayesian cognitive science is a research programme that relies on modelling resources from Bayesian statistics for studying and understanding mind, brain, and behaviour. Conceiving of mental capacities as computing solutions to inductive problems, Bayesian cognitive scientists develop probabilistic models of mental capacities and evaluate their adequacy based on behavioural and neural data generated by humans (or other cognitive agents) performing a pertinent task. The overarching goal is to identify the mathematical principles, algorithmic procedures, and causal mechanisms (...) that enable cognitive agents to take uncertainty into account and weigh it appropriately in producing adaptive behaviour. -/- The appeal of Bayesian cognitive science derives from its transparency, normativity, and unifying power. Resources from Bayesian statistics allow cognitive scientists to characterise transparently, in terms of random variables and probabilistic dependencies between them, the inductive problems that many mental capacities are presumed to solve. Given this characterisation, researchers can define an upper bound on one’s performance on that problem and use it as a benchmark for interpreting experimental results, formulating hypotheses about why and when deviations from optimal performance should be expected, and seeking explanations of mental capacities within one encompassing theoretical framework. -/- Although critics question the testability, explanatory power, and plausibility of Bayesian models of mental capacities, Bayesian cognitive science has proved itself to be an incredibly fruitful research programme. Fuelled by empirical and theoretical results from psychology, neuroscience, philosophy, computer science, artificial intelligence, and evolution, Bayesian cognitive science has: advanced our understanding of why cognitive systems should keep track of uncertainty and use it to facilitate adaptive behaviour; clarified how the brain might encode information about the uncertainty of its stimuli and perform computations with probability distributions; and crystallised the insight that cognitive agents’ management of uncertainty might be grounded in predictive processes aimed at avoiding surprising exchanges with the environment. (shrink)

Expressions are synonymous if they have the same semantic content. Complex expressions are synonymously isomorphic in Alonzo Church’s sense if one is obtainable from the other by a sequence of alphabetic changes of bound variables or replacements of component expressions by syntactically simple synonyms. Synonymous isomorphism provides a very strict criterion for synonymy of sentences. Several eminent philosophers of language hold that synonymous isomorphism is not strict enough. These philosophers hold that ‘Greeks prefer Greeks’ and ‘Greeks prefer Hellenes’ express different (...) propositions even if they are synonymously isomorphic. They hold that the very recurrence (multiple occurrence) of ‘Greeks’ contributes to the proposition expressed something that indicates the very recurrence in question. Kit Fine argues that this thesis, which he labels semantic relationism calls for a radically new conception of semantics. I have argued that the relevant phenomenon is wholly pragmatic, entirely non-semantic. Here I supplement the case with a new argument. No cognition without recognition—or almost none. With this observation, standard Millianism has sufficient resources to confront Frege’s puzzle and related problems without injecting pragmatic phenomena where they do not belong. (shrink)

The aim of this article is to show that externalist accounts of cognition such as Clark and Chalmers' (1998) “active externalism” lead to an explosion of knowledge that is caused by online resources such as Wikipedia and Google. I argue that externalist accounts of cognition imply that subjects who integrate mobile Internet access in their cognitive routines have millions of standing beliefs on unexpected issues such as the birth dates of Moroccan politicians or the geographical coordinates of villages (...) in southern Indonesia. Although many externalists propose criteria for the bounds of cognition that are designed to avoid this explosion of knowledge, I argue that these criteria are flawed and that active externalism has to accept that information resources such as Wikipedia and Google constitute extended cognitive processes. (shrink)

An increasingly prevalent approach to studying human cognition is to construe the mind as optimally allocating limited cognitive resources among cognitive processes. Under this bounded rationality approach (Icard in Philos Sci 85(1):79–101, 2018; Simon in Utility and probability, Palgrave Macmillan, 1980), it is common to assume that resource-bounded cognitive agents approximate normative solutions to statistical inference problems, and that much of the bias and variability in human performance can be explained in terms of the (...) approximation strategies we employ. In this paper, we argue that this approach restricts itself to an unnecessarily narrow scope of cognitive models, which limits its ability to explain how humans flexibly adapt their representations to novel environments. We argue that more attention should be paid to how we form our cognitive representations in the first place, and advocate for pluralistic framework which jointly optimizes over both representations and algorithms for manipulating them. We identify several fundamental trade-offs that manifest in this joint optimization, and draw on recent work to motivate a unified formal framework for this analysis. We illustrate a simplified version of this analysis with a case study in social cognition, and outline several new directions for research that this approach suggests. (shrink)

How much would you pay to play a lottery with an “infinite expected payoff?” In the case of the century old, St. Petersburg Paradox, the answer is that the vast majority of people would only pay a small amount. The authors seek to understand this paradox by providing an explanation consistent with a broad, process‐level model of human decision‐making under risk.

It is known that, on average, people adapt their choice of memory strategy to the subjective utility of interaction. What is not known is whether an individual's choices are boundedly optimal. Two experiments are reported that test the hypothesis that an individual's decisions about the distribution of remembering between internal and external resources are boundedly optimal where optimality is defined relative to experience, cognitive constraints, and reward. The theory makes predictions that are tested against data, not fitted to (...) it. The experiments use a no-choice/choice utility learning paradigm where the no-choice phase is used to elicit a profile of each participant's performance across the strategy space and the choice phase is used to test predicted choices within this space. They show that the majority of individuals select strategies that are boundedly optimal. Further, individual differences in what people choose to do are successfully predicted by the analysis. Two issues are discussed: the performance of the minority of participants who did not find boundedly optimal adaptations, and the possibility that individuals anticipate what, with practice, will become a bounded optimal strategy, rather than what is boundedly optimal during training. (shrink)

In this paper we design a new logical system to explicitly model the different deductive reasoning steps of a boundedly rational agent. We present an adequate system in line with experimental findings about an agent’s reasoning limitations and the cognitive effort that is involved. Inspired by Dynamic Epistemic Logic, we work with dynamic operators denoting explicit applications of inference rules in our logical language. Our models are supplemented by (a) impossible worlds (not closed under logical consequence), suitably structured according (...) to the effect of inference rules, and (b) quantitative components capturing the agent’s cognitive capacity and the cognitive costs of rules with respect to certain resources (e.g. memory, time). These ingredients allow us to avoid problematic logical closure principles, while at the same time deductive reasoning is reflected in our dynamic truth clauses. We further show that our models can be reduced to awareness-like plausibility structures that validate the same formulas and we give a sound and complete axiomatization with respect to them. This approach to the agent’s internal deductive reasoning is finally combined with actions of external information. (shrink)

This paper presents an attempt to bridge the gap between logical and cognitive treatments of strategic reasoning in games. There have been extensive formal debates about the merits of the principle of backward induction among game theorists and logicians. Experimental economists and psychologists have shown that human subjects, perhaps due to their bounded resources, do not always follow the backward induction strategy, leading to unexpected outcomes. Recently, based on an eye-tracking study, it has turned out that even (...) human subjects who produce the outwardly correct ‘backward induction answer’ use a different internal reasoning strategy to achieve it. The paper presents a formal language to represent different strategies on a finer-grained level than was possible before. The language and its semantics help to precisely distinguish different cognitive reasoning strategies, that can then be tested on the basis of computational cognitive models and experiments with human subjects. The syntactic framework of the formal system provides a generic way of constructing computational cognitive models of the participants of the Marble Drop game. (shrink)

Building upon the foundations laid by Russell, Donnellan, Chastain, and more recently, Almog, this paper addresses key questions about the basic mechanism by which we think of worldly objects, and (in contrast to many connected projects), does so in isolation from questions about how we speak of them. I outline and defend a view based on the notion of bound cognition. Bound cognition, like perception, is world-to-mind in the sense that it is generated by the item being thought of rather (...) than by the mind doing the thinking. It is a direct, two-place, non-representational relation, and it is prior to any epistemic connection between the thinker and the object of thought. Although the paradigm case for bound cognition involves sensory perception of an individual, I argue that the cognitive relations falling under the heading of bound cognition also include non-perceptual cognitive relations (such as the relation between a thinker and a historical individual) as well as cognitive relations to non-individuals (such as pairs, pluralities, species, and features). Four illustrative cases are discussed, and anticipated worries about abstract and empty cases are addressed. (shrink)

This book deals with the theoretical, methodological, and empirical implications of bounded rationality in the operation of institutions. It focuses on decisions made under uncertainty, and presents a reliable strategy of knowledge acquisition for the design and implementation of decision-support systems. Based on the distinction between the inner and outer environment of decisions, the book explores both the cognitive mechanisms at work when actors decide, and the institutional mechanisms existing among and within organizations that make decisions fairly predictable. (...) While a great deal of work has been done on how organizations act as patterns of events for (boundedly) rational decisions, less effort has been devoted to study under which circumstances organizations cease to act as such reliable mechanisms. Through an empirical strategy on open-ended response data from a survey among junior judges, the work pursues two main goals. The first one is to explore the limits of "institutional rationality" of the Spanish lower courts on-call service, an optimal scenario to observe decision-making under uncertainty. The second aim is to achieve a better understanding of the kind of uncertainty under which inexperienced decision-makers work. This entails exploring the demands imposed by problems and the knowledge needed to deal with them, making this book also a study on expertise achievement in institutional environments. This book combines standard multivariate statistical methods with machine learning techniques such as multidimensional scaling and topic models, treating text as data. Doing so, the book contributes to the collaboration between empirical social scientific approaches and the community of scientists that provide the set of tools and methods to make sense of the fastest growing resource of our time: data. (shrink)

“Rationality” in Simon's “bounded rationality” is the principle that humans make decisions on the basis of step-by-step reasoning using systematic rules of logic to maximize utility. “Bounded rationality” is the observation that the ability of a human brain to handle algorithmic complexity and large quantities of data is limited. Bounded rationality, in other words, treats a decision maker as a machine carrying out computations with limited resources. Under the principle of embodied cognition, a cognitive mind (...) is an interactive machine. Turing-Church computations are not interactive, and interactive machines can accomplish things that no Turing-Church computation can accomplish. Hence, if “rationality” is computation, and “bounded rationality” is computation with limited complexity, then “embodied bounded rationality” is both more limited than computation and more powerful. By embracing interaction, embodied bounded rationality can accomplish things that Turing-Church computation alone cannot. Deep neural networks, which have led to a revolution in artificial intelligence, are both interactive and not fundamentally algorithmic. Hence, their ability to mimic some cognitive capabilities far better than prior algorithmic techniques based on symbol manipulation provides empirical evidence for the principle of embodied bounded rationality. (shrink)

This work is an initial step toward developing a cognitive theory of cyber deception. While widely studied, the psychology of deception has largely focused on physical cues of deception. Given that present‐day communication among humans is largely electronic, we focus on the cyber domain where physical cues are unavailable and for which there is less psychological research. To improve cyber defense, researchers have used signaling theory to extended algorithms developed for the optimal allocation of limited defense resources by (...) using deceptive signals to trick the human mind. However, the algorithms are designed to protect against adversaries that make perfectly rational decisions. In behavioral experiments using an abstract cybersecurity game (i.e., Insider Attack Game), we examined human decision‐making when paired against the defense algorithm. We developed an instance‐based learning (IBL) model of an attacker using the Adaptive Control of Thought‐Rational (ACT‐R) cognitive architecture to investigate how humans make decisions under deception in cyber‐attack scenarios. Our results show that the defense algorithm is more effective at reducing the probability of attack and protecting assets when using deceptive signaling, compared to no signaling, but is less effective than predicted against a perfectly rational adversary. Also, the IBL model replicates human attack decisions accurately. The IBL model shows how human decisions arise from experience, and how memory retrieval dynamics can give rise to cognitive biases, such as confirmation bias. The implications of these findings are discussed in the perspective of informing theories of deception and designing more effective signaling schemes that consider human bounded rationality. (shrink)

We conducted a computer-based psychological experiment in which a random mix of 40 tautologies and 40 non-tautologies were presented to the participants, who were asked to determine which ones of the formulas were tautologies. The participants were eight university students in computer science who had received tuition in propositional logic. The formulas appeared one by one, a time-limit of 45 s applied to each formula and no aids were allowed. For each formula we recorded the proportion of the participants who (...) classified the formula correctly before timeout and the mean response time among those participants. We propose a new proof formalism for modeling propositional reasoning with bounded cognitive resources. It models declarative memory, visual memory, working memory, and procedural memory according to the memory model of Atkinson and Shiffrin and reasoning processes according to the model of Newell and Simon. We also define two particular proof systems, T and NT, for showing propositional formulas to be tautologies and non-tautologies, respectively. The accuracy was found to be higher for non-tautologies than for tautologies ( p T was.89 and for non-tautologies the correlation between latency and minimum proof length in NT was.87. (shrink)

Marr's levels of analysis—computational, algorithmic, and implementation—have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push (...) the notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call “resource-rational analysis.”. (shrink)

First, we describe a psychological experiment in which the participants were asked to determine whether sentences of first-order logic were true or false in finite graphs. Second, we define two proof systems for reasoning about truth and falsity in first-order logic. These proof systems feature explicit models of cognitive resources such as declarative memory, procedural memory, working memory, and sensory memory. Third, we describe a computer program that is used to find the smallest proofs in the aforementioned proof (...) systems when capacity limits are put on the cognitive resources. Finally, we investigate the correlation between a number of mathematical complexity measures defined on graphs and sentences and some psychological complexity measures that were recorded in the experiment. (shrink)

In recent years, the human ability to reasoning about mental states of others in order to explain and predict their behavior has come to be a highly active area of research. Researchers from a wide range of fields { from biology and psychology through linguistics to game theory and logic{ contribute new ideas and results. This interdisciplinary workshop, collocated with the Thirteenth International Conference on Theoretical Aspects of Rationality and Knowledge (TARK XIII), aims to shed light on models of social (...) reasoning that take into account realistic resource bounds. People reason about other people's mental states in order to understand and predict the others' behavior. This capability to reason about others' knowledge, beliefs and intentions is often referred to as theory of mind. Idealized rational agents are capable of recursion in their social reasoning, and can reason about phenomena like common knowledge. Such idealized social reasoning has been modeled by modal logics such as epistemic logic and BDI (belief, desire, intention) logics and by epistemic game theory. However, in real-world situations, many people seem to lose track of such recursive social reasoning after only a few levels. The workshop provides a forum for researchers that attempt to analyze, understand and model how resource-bounded agents reason about other minds. (shrink)

In the past 10 years, contemporary philosophy of mathematics has seen the development of a trend that conceives mathematics as first and foremost a human activity and in particular as a kind of practice. However, only recently the need for a general framework to account for the target of the so-called philosophy of mathematical practice has emerged. The purpose of the present article is to make progress towards the definition of a more precise general framework for the philosophy of mathematical (...) practice by exploring two strategies. A first strategy is to turn to philosophy of mind and Edwin Hutchins' view of distributed cognition in order to better understand the cognitive issues at play when considering a community of mathematicians; a second strategy is to refer to philosophy of language and focus on Robert Brandom's inferentialism and mathematical conceptual content. A possible combination of these two views, called enhanced material inferentialism, is then put forward as a promising framework to account for the philosophy of mathematical practice. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Toward Resilient DemocracyCognitive Resources and ConstraintsJohn Teehan (bio)I. Introduction: The Cognitive Science of ReligionAmerican Immanence, an important and insightful work, offers an analysis of the existential crisis facing American democracy, and a possible path through this crisis. In developing this path, Michael Hogue asks, "can the feeling and awareness of the precarious value of life …awaken us to the precious depths of immanence, to living as if (...) this, our one and only world, matters ultimately?"1 Such an awakening, he argues, is vital to developing a "resilient democracy." I believe the answer to his question is "yes," and a positive answer to this profound question is sufficient warrant for exploring the path Hogue sets out. However, there is another question, one with broader implications: can this moral vision be adopted on a wide enough scale to attain the critical mass necessary to develop a democracy sufficiently resilient to weather this crisis? I will explore this second question using the insights derived from cognitive science, and particularly from the cognitive science of religion. This approach picks up on Hogue's invitation to interpret religion "within the evolutionary contexts of natural history,"2 and concurs with his claim that in "demystifying religion" an "evolutionary account …opens the way to a religious experience."3The Cognitive Science of Religion (CSR) is grounded in an evolutionary understanding of human cognitive and emotional processes, as these processes have developed to enable the species to respond to the challenges of survival and reproduction in dynamic environments, both physical and social. These cognitive tools were not shaped to discern some pre-given reality, but rather to serve the practical goals of natural beings embedded in natural situations. CSR, then, is congruent with the immanental philosophy, grounded in pragmatism, that Hogue develops in his book. Indeed, it can be argued that the methodology of CSR implicitly entails a pragmatist epistemology4. The various [End Page 65] mental tools and resultant religious beliefs and rituals all serve the ultimate goal of successful action within natural situations. CSR, then, can provide an empirical account of at least some of the processes that would be involved in actualizing an immanental political theology, and may identify some of the cognitive obstacles to that project.It is beyond the scope of this essay to set out a detailed account of CSR, but it will suffice to introduce some general tenets that have played a seminal role in the field.5 Those elements of a cultural system that we would deem religious are derived from natural cognitive processes that evolved to allow our earliest ancestors to successfully navigate an uncertain and dangerous environment.6 As an example, let's consider the gods, understanding by the "gods" any of the various beings that might commonly be termed "supernatural" (e.g., gods, spirits, ghosts, demons, fairies, divine ancestors, etc.). Belief in gods is theorized to flow, in part, from natural cognitive mechanisms for the detection of agents (that is, beings that act with intent). The ability to detect such beings—beings that might pose a danger—is essential to surviving in an uncertain and dangerous world. This ability was so vital that natural selection favored the evolution of a cognitive process for detecting agents that is hypersensitive.7 Detecting the presence of an agent when none is actually present is a much safer error than failing to detect an actual predator, and so this cognitive strategy could regularly give rise to false positives.Detecting the presence of an agent is the beginning phase of devising effective action, but to determine how to respond to this perceived agent, we must make sense of its possible intent. Therefore, we do not merely perceive a presence, we ascribe intention and purpose to that agent. In doing so, we engage the mental process termed Theory of Mind (ToM).8 Detecting the [End Page 66] action of agents, and determining intention and purpose, are vital to successful action. In a dangerous and uncertain world—i.e. the world in which humans have lived for millennia—these skills are essential to survival, and it follows that natural selection would favor cognitive processes that erred on the side of... (shrink)

A critique of the hypothesis of extended cognition.

This paper consists of a detailed analysis of how the participants in a debate build their emotional position during the interaction and how such a position is strongly related to the conclusion they defend. In this case study, teenage Mexican, students, arguing about access to drinking water, display extensive discursive work on the emotional tonality given to the issue. Plantin’s methodological tools are adopted to follow two alternative emotional framings produced by disagreeing students, starting from a common, highly negative, thymic (...) tonality. Through the analysis of four parameters we describe how the emotional dimension of schematization is argumentatively relevant. In authentic discourse, it is impossible to separate emotion from reason. The conclusion section discusses the implications for the design of argumentation-based pedagogical activities. (shrink)

(2013). Evolutionary modules and Bayesian facilitation: The role of general cognitive resources. Thinking & Reasoning: Vol. 19, No. 1, pp. 27-53. doi: 10.1080/13546783.2012.713177.

This study examines the cognitive resources underlying the attribution of stigma in substance use and misuse. A cultural model of substance misuse risk was elicited from students at a major U.S. state university. We found a contested cultural model, with some respondents adopting a model of medical risk while others adopted a model of moral failure; agreeing that moral failure primarily defined risk led to greater attribution of stigma. Here we incorporate general beliefs about moral decision-making, assessed through (...) Moral Foundations Theory. Specifically, we examined commitment to each moral foundation in relation to stigma attribution while controlling for the specific model of substance misuse risk. We found an interaction between the purity moral foundation and the cultural model of risk. This suggests that broad moral orientations, along with more specific understandings of substance misuse risk, combine to orient an individual with respect to stigma attribution. (shrink)

An alarming number of philosophers and cognitive scientists have argued that mind extends beyond the brain and body. This book evaluates these arguments and suggests that, typically, it does not. A timely and relevant study that exposes the need to develop a more sophisticated theory of cognition, while pointing to a bold new direction in exploring the nature of cognition Articulates and defends the “mark of the cognitive”, a common sense theory used to distinguish between cognitive and (...) non-cognitive processes Challenges the current popularity of extended cognition theory through critical analysis and by pointing out fallacies and shortcoming in the literature Stimulates discussions that will advance debate about the nature of cognition in the cognitive sciences. (shrink)

Orthodox Bayesianism is a highly idealized theory of how we ought to live our epistemic lives. One of the most widely discussed idealizations is that of logical omniscience: the assumption that an agent’s degrees of belief must be probabilistically coherent to be rational. It is widely agreed that this assumption is problematic if we want to reason about bounded rationality, logical learning, or other aspects of non-ideal epistemic agency. Yet, we still lack a satisfying way to avoid logical omniscience (...) within a Bayesian framework. Some proposals merely replace logical omniscience with a different logical idealization; others sacrifice all traits of logical competence on the altar of logical non-omniscience. We think a better strategy is available: by enriching the Bayesian framework with tools that allow us to capture what agents can and cannot infer given their limited cognitive resources, we can avoid logical omniscience while retaining the idea that rational degrees of belief are in an important way constrained by the laws of probability. In this paper, we offer a formal implementation of this strategy, show how the resulting framework solves the problem of logical omniscience, and compare it to orthodox Bayesianism as we know it. (shrink)