In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of working memory (...) to show how modeling has progressed over the years. The methodological assumptions of new modeling work are best understood in the mechanistic framework, which is evidenced by the way in which models are empirically validated. Moreover, the methodological and theoretical progress in computational neuroscience vindicates the new mechanistic approach to explanation, which, at the same time, justifies the best practices of computational modeling. Overall, computational modeling is deservedly successful in cognitive science. Its successes are related to deep conceptual connections between cognition and computation. Computationalism is not only here to stay, it becomes stronger every year. (shrink)

The past three decades have witnessed a remarkable growth of research interest in the mind. This trend has been acclaimed as the ‘cognitive revolution’ in psychology. At the heart of this revolution lies the claim that the mind is a computational system. The purpose of this paper is both to elucidate this claim and to evaluate its implications for cognitive psychology. The nature and scope of cognitive psychology and cognitive science are outlined, the principal assumptions underlying the information processing approach (...) to cognition are summarised and the nature of artificial intelligence and its relationship to cognitive science are explored. The ‘computational metaphor’ of mind is examined and both the theoretical and methodological issues which it raises for cognitive psychology are considered. Finally, the nature and significance of ‘connectionism’—the latest paradigm in cognitive science—are briefly reviewed. (shrink)

The Computational Metaphor is an extremely influential notion, and more than any other trend has given rise to the field of Cognitive Science. Environmentalism is at present better formalised as a political movement than as a scientific paradigm, despite significant research by Gibson and his followers. This article attempts to address the difficult problem of synthesising these two apparently antagonistic research paradigms.

Behaviour is often described as the computation of a response to a stimulus. This description is incomplete in an important way because it only examines what occurs between the reception of stimulus information and the generation of an action. Behaviour is more correctly described as a control process where actions are performed in order to affect perceptions. This closed-loop nature of behaviour is de-emphasized in modern discussions of brain function, leading to a number of artificial mysteries. A notable example is (...) the ‘symbol grounding problem'. When behaviour is viewed as a control process, it is natural to explain how internal representations, even symbols, can have meaning for an organism, and how actions can be motivated by organic needs. (shrink)

his article will focus on the mechanistic origins of the computer metaphor, which forms the conceptual framework for the methodology of the cognitive sciences, some areas of artificial intelligence and the philosophy of mind. The connection between the history of computing technology, epistemology and the philosophy of mind is expressed through the metaphorical dictionaries of the philosophical discourse of a particular era. The conceptual clarification of this connection and the substantiation of the mechanistic components of the computer (...) metaphor is the main goal of this article. The statement is substantiated that the invention of mechanical computing devices, having a long history in the European engineering tradition, formed the prerequisites for the emergence of machine functionalism in the modern philosophy of mind. The idea of multiple implementation stems from the principle that a formal symbol system prescribes rules for the use of rational abstractions through the physical architecture of a computational engine. The article considers the reasons for the conceptual shift and reveals the semantic foundations for the metaphorical transfer of the properties of abstract objects from the theory of automata to the field of modern philosophy of mind. The criticism and ways of protecting the philosophical program of machine functionalism are analyzed by changing the content of the metaphor “Mind as machine”. The reasons for the stability of the information-computer approach in cognitive sciences are also disclosed and explained. (shrink)

This paper affirms human enhancement in principle, but questions the inordinate attention paid to two particular forms of enhancement: life extension and raising IQ. The argument is not about whether these enhancements are possible or not; instead, I question the aspirations behind the denial of death and the stress on one particular type of intelligence: the logico-analytic. Death is a form of finitude, and finitude is a crucially defining part of human life. As for intelligence, Howard Gardner and Daniel Goleman (...) show us the importance of multiple intelligences. After clarifying the notion of different psychological types, the paper takes five specimens of a distinct type and then studies the traits of that type through their examples. Seeking a pattern connecting those traits, the paper finds them bound together by the embrace of the computational metaphor for human cognition and then argues that the computational metaphor does not do a good job of describing human intelligence. Enlisting the works of Jaron Lanier and Ellen Ullman, the paper ends with a caution against pushing human intelligence toward machine intelligence, and points toward the human potential movement as a possible ally and wise guide for the transhumanist movement. (shrink)

(Penultimate draft) Embodied Cognition holds that bodily (e.g. sensorimotor) states and processes are directly involved in some higher-level cognitive functions (e.g. reasoning). This challenges traditional views of cognition according to which bodily states and processes are, at most, indirectly involved in higher-level cognition. Although some elements of Embodied Cognition have been integrated into mainstream cognitive science, others still face adamant resistance. In this paper, rather than straightforwardly defend Embodied Cognition against specific objections I will do the following. First, I will (...) present a concise account of embodied conceptual processing and highlight some of its advantages over non-embodied accounts, specifically focusing on the role of metaphors. Second, I will detail the influence of computational metaphors on theories of cognition and evaluation of these theories. Third, I will argue that embodied cognitive mechanisms, specifically those operating through computational metaphors, may drive some of the resistance to Embodied Cognition - and that Embodied Cognition is able to offer a uniquely compelling account of this. Ultimately, this will contribute to an improved understanding of Embodied Cognition, its explanatory power, and how it ought to be evaluated. Additionally, it will shed light on the role of metaphors in shaping philosophical thought and highlight the importance of these influences. (shrink)

The arguments of this article are developed in detail in the chapters II, 3.3 and IV, 3 of my book KRITIK DES NATURALISMUS, Berlin/New York (de Gruyter) 1993.

The article presents preliminary results of the conceptual analysis of the mechanistic profile of the computer metaphor. Mechanic reductionism is a special direction of computer metaphor rooted in various historical forms of word usage. Here we trace the stages of formation of the principles of transferring the properties of a mechanical computer to the properties of the human body and mind. We are also trying to identify the basic principles of semantic transfer, which have survived (...) to this day in the discourse of modern computationalism. The reasons are analyzed due to which the metaphor «Human (body) is machine», traditional for the Modern Age, was transformed into a more complex version of «Mind is machine». What happened to the concepts of «mind» and «machine»? How have ideas about the properties of computational procedures changed? What keeps the counterintuitive computer metaphor viable today? The answers to this series of questions and theoretical ways of solving these problems are contained in this paper. (shrink)

Recent metaphor research has revealed that metaphor comprehension involves both categorization and comparison processes. This finding has triggered the following central question: Which property determines the choice between these two processes for metaphor comprehension? Three competing views have been proposed to answer this question: the conventionality view (Bowdle & Gentner, 2005), aptness view (Glucksberg & Haught, 2006b), and interpretive diversity view (Utsumi, 2007); these views, respectively, argue that vehicle conventionality, metaphor aptness, and interpretive diversity determine the (...) choice between the categorization and comparison processes. This article attempts to answer the question regarding which views are plausible by using cognitive modeling and computer simulation based on a semantic space model. In the simulation experiment, categorization and comparison processes are modeled in a semantic space constructed by latent semantic analysis. These two models receive word vectors for the constituent words of a metaphor and compute a vector for the metaphorical meaning. The resulting vectors can be evaluated according to the degree to which they mimic the human interpretation of the same metaphor; the maximum likelihood estimation determines which of the two models better explains the human interpretation. The result of the model selection is then predicted by three metaphor properties (i.e., vehicle conventionality, aptness, and interpretive diversity) to test the three views. The simulation experiment for Japanese metaphors demonstrates that both interpretive diversity and vehicle conventionality affect the choice between the two processes. On the other hand, it is found that metaphor aptness does not affect this choice. This result can be treated as computational evidence supporting the interpretive diversity and conventionality views. (shrink)

This essay is an attempt to understand how technological metaphors, particularly computer metaphors, are relevant to moral education. After discussing various types of technological metaphors, it is argued that technological metaphors enter moral thought through their functional descriptions. The computer metaphor is then explored by turning to the hacker ethic. Analysis of this ethic reveals parallels between the experience of computer programming and the moral standards of those who are enmeshed in computer technology. This parallel (...) suggests that the hacker ethic is being pushed by a computer metaphor and its functional descriptions in a direction of individualism and systems thinking. After examining some possible implications of the computer metaphor, this essay offers suggestions concerning how technological metaphors may be critiqued. (shrink)

The target article by Leech et al. presents a compelling computational theory of analogy-making. However, there is a key difficulty that persists in theoretical treatments of analogy-making, computational and otherwise: namely, the lack of a detailed account of the neurophysiological mechanisms that give rise to analogy behavior. My commentary explores this issue.

ABSTRACTIn this article we investigate structural differences between “literary” metaphors created by renowned poets and “nonliterary” ones imagined by non-professional authors from Katz et al.’s 1988 corpus. We provide data from quantitative narrative analyses of the altogether 464 metaphors on over 70 variables, including surface features like metaphor length, phonological features like sonority score, or syntactic-semantic features like sentence similarity. In a first computational study using machine learning tools we show that Katz et al.’s literary metaphors can be successfully (...) discriminated from their nonliterary ones on the basis of response measures, in particular the ratings for familiarity, ease of interpretation, semantic relatedness, and comprehensibility. A second computational study then shows that the classifier can reliably detect and predict between-group differences on the basis of five QNA features generalizing from a... (shrink)

ABSTRACTComputers are now able to automatically generate metaphors, but some automatically generated metaphors are more well received than others. In this article, we showed participants a series of “A is B” type metaphors that were either generated by humans or taken from the Twitter account “MetaphorIsMyBusiness”, which is linked to a fully automated metaphor generator. We used these metaphors to assess linguistic factors that drive metaphor appreciation and understanding, including the role of novelty, word frequency, concreteness, and emotional (...) valence of the topic and vehicle terms. We additionally assessed how these metaphors were understood in three languages, including English, Spanish, and Mandarin Chinese, and whether participants thought they had been generated by a human or a computer. We found that meaningfulness, appreciation, speed in finding meaning, and humanness ratings were reliably correlated with each other in all three languages, which we interpret to indicate a mor... (shrink)

Powerful transformer models based on neural networks such as GPT-4 have enabled huge progress in natural language processing. This paper identifies three challenges for computer programs dealing with metaphors. First, the phenomenon of Twice-Apt-Metaphors shows that metaphorical interpretations do not have to be triggered by syntactical, semantic or pragmatic tensions. The detection of these metaphors seems to involve a sense of aesthetic pleasure or a higher-order theory of mind, both of which are difficult to implement into computer programs. (...) Second, the contexts relative to which metaphors are interpreted are not simply given but must be reconstructed based on pragmatic considerations that can involve presuppositional pretence. If computer programs cannot produce or understand such a form of pretence, they will have problems dealing with certain metaphors. Finally, adequately interpreting and reacting to some metaphors seems to require the ability to have internal, first-personal experiential and affective states. Since it is questionable whether computer programs have such mental states, it can be assumed that they will have problems with these kinds of metaphors. (shrink)

In this paper we start from the assumption that in a metaphor, or an analogy, some terms belonging to one domain (source domain) are used to refer to objects other than their conventional referents belonging to a possibly different domain (target domain). We describe a formalism, which is based on the First Order Predicate Calculus, for representing the knowledge structure associated with a domain and then develop a theory of Constrained Semantic Transference [CST] which allows the terms and the (...) structural relationships of the source domain to be transferred coherently across to the target domain. We show how metaphors and analogies can be characterized in CST in such a way that many of their cognitive properties con be explained.We then propose a theory of Approximate Semantic Transference [AST] which is a computational version of CST and is derived from it by replacing the coherency requirement with approximate coherency. We show how AST can be used as a basis for designing models of cognitive processes involved in comprehending metaphors and analogies. (shrink)

Biologically motivated computing seeks to transfer ideas from the biosciences to computer science. In seeking to make transfers it is helpful to be able to appreciate the metaphors which people use. This is because metaphors provide the context through which analogies and similes are made and by which many scientific models are constructed. As such, it is important for any rapidly evolving domain of knowledge to have developments accounted for in these terms. This paper seeks to provide one overview (...) of the process of modelling and shows how it can be used to account for a variety of biologically motivated computational models. Certain key ideas are identified in the subsequent analysis of biological sources, notably, systemic metaphors. Three important aspects of biological thinking are then considered in the light of computer science applications: biological organization, the cell, and models of evolution. The analysis throughout the paper is descriptive rather than formalized so that a large variety of potential applications may be considered. (shrink)

The duality of computer programs is characterized, on the one hand, by their physical implementations on physical devices, and, on the other, by the conceptual implementations in programmers’ minds of the objects making up the computational processes they conceive. We contend that central to programmers’ conceptual implementations are (i) the concept of type, at both the programming and the design level, and (ii) metaphors created to facilitate these implementations.

Empirical analyses have provided some important constraints for computational theories of metaphor. Three such constraints relate to (1) the similar processing time for literal and metaphorical language, (2) the time‐limited processing of many metaphors, and (3) the dissociation of metaphor comprehension and appreciation. Indurkhya's (1986, 1987) model is discussed with respect to these issues.

The language used to talk about computers is uniquely colorful and sometimes extraordinarily difficult. This paper examines ‘computer discourse’ and points out its highly metaphorical nature. While the use of metaphor is unavoidable, it often leads, especially in informal settings, to the mannered use of words we call jargon. Metaphor becomes jargon when it is used too literally in a self-conscious manner. Experts often use their metaphors as though they were literally true. Technical details fall away and (...) the metaphor is taken for the reality it represents. The less expert sometimes mimic the language they hear, in a self-conscious manner, without truly understanding it. (shrink)

Metaphor's peculiar property to yield cognitive insight-- often in otherwise false sentences -- has been the focus of contemporary studies of metaphor. In Metaphor: Its Linguistic Structure and Cognitive Force, Eva Kittay develops the semantic field theory of metaphor (SFTM). The task of the present work is to formalize some of the central claims of SFTM. Formalization forces us to make the central concepts of SFTM precise and operational, and it enables us to evaluate the consistency (...) and explanatory power of SFTM through empirical testing. To empirically test our formalization of SFTM, we constructed a working computer program from it. This program, called NETMET, is highly successful in generating syntactically complex and semantically interesting metaphors. Its success provides empirical confirmation of SFTM. (shrink)

Language understanding is one of the most important characteristics for human beings. As a pervasive phenomenon in natural language, metaphor is not only an essential thinking approach, but also an ingredient in human conceptual system. Many of our ways of thinking and experiences are virtually represented metaphorically. With the development of the cognitive research on metaphor, it is urgent to formulate a computational model for metaphor understanding based on the cognitive mechanism, especially with the view to promoting (...) natural language understanding. Many works have been done in pragmatics and cognitive linguistics, especially the discussions on metaphor understanding process in pragmatics and metaphor mapping representation in cognitive linguistics. In this paper, a theoretical framework for metaphor understanding based on the embodied mechanism of concept inquiry is proposed. Based on this framework, ontology is introduced as the knowledge representation method in metaphor understanding, and metaphor mapping is formulated as ontology mapping. In line with the conceptual blending theory, a revised conceptual blending framework is presented by adding a lexical ontology and context as the fifth mental space, and a metaphor mapping algorithm is proposed. (shrink)

How are natural symbol systems best understood? Traditional “symbolic” approaches seek to understand cognition by analogy to highly structured, prescriptive computer programs. Here, we describe some problems the traditional computational metaphor inevitably leads to, and a very different approach to computation (Ramscar, Yarlett, Dye, Denny, & Thorpe, 2010; Turing, 1950) that allows these problems to be avoided. The way we conceive of natural symbol systems depends to a large degree on the computational metaphors we use to understand them, (...) and machine learning suggests an understanding of symbolic thought that is very different to traditional views (Hummel, 2010). The empirical question then is: Which metaphor is best? (shrink)

Metaphors that compare the computer to a human brain are common in computer science and can be traced back to a fertile period of research that unfolded after the Second World War. To conceptualize the emerging “intelligent” properties of computing machines, researchers of the era created a series of virtual objects that served as interpretive devices for representing the immaterial functions of the computer. This paper analyses the use of the terms “artificial” and “virtual” in scientific papers, (...) textbooks, and popular articles of the time, and examines how, together, they shaped models in computer science used to conceptualize computer processes. (shrink)

Genes are often described by biologists using metaphors derived from computa- tional science: they are thought of as carriers of information, as being the equivalent of ‘‘blueprints’’ for the construction of organisms. Likewise, cells are often characterized as ‘‘factories’’ and organisms themselves become analogous to machines. Accordingly, when the human genome project was initially announced, the promise was that we would soon know how a human being is made, just as we know how to make airplanes and buildings. Impor- tantly, (...) modern proponents of Intelligent Design, the latest version of creationism, have exploited biologists’ use of the language of information and blueprints to make their spurious case, based on pseudoscientific concepts such as ‘‘irreducible complexity’’ and on flawed analogies between living cells and mechanical factories. However, the living organ- ism = machine analogy was criticized already by David Hume in his Dialogues Concerning Natural Religion. In line with Hume’s criticism, over the past several years a more nuanced and accurate understanding of what genes are and how they operate has emerged, ironically in part from the work of computational scientists who take biology, and in particular developmental biology, more seriously than some biologists seem to do. In this article we connect Hume’s original criticism of the living organism = machine analogy with the modern ID movement, and illustrate how the use of misleading and outdated metaphors in science can play into the hands of pseudoscientists. Thus, we argue that dropping the blueprint and similar metaphors will improve both the science of biology and its understanding by the general public. (shrink)

A formal model of metaphor is introduced. It models metaphor, first, as an interaction of “frames” according to the frame semantics, and then, as a wave function in Hilbert space. The practical way for a probability distribution and a corresponding wave function to be assigned to a given metaphor in a given language is considered. A series of formal definitions is deduced from this for: “representation”, “reality”, “language”, “ontology”, etc. All are based on Hilbert space. A few (...) statements about a quantum computer are implied: The sodefined reality is inherent and internal to it. It can report a result only “metaphorically”. It will demolish transmitting the result “literally”, i.e. absolutely exactly. A new and different formal definition of metaphor is introduced as a few entangled wave functions corresponding to different “signs” in different language formally defined as above. The change of frames as the change from the one to the other formal definition of metaphor is interpreted as a formal definition of thought. Four areas of cognition are unified as different but isomorphic interpretations of the mathematical model based on Hilbert space. These are: quantum mechanics, frame semantics, formal semantics by means of quantum computer, and the theory of metaphor in linguistics. (shrink)

The journal of Cognitive Computation is defined in part by the notion that biologically inspired computational accounts are at the heart of cognitive processes in both natural and artificial systems. Many studies of various important aspects of cognition (memory, observational learning, decision making, reward prediction learning, attention control, etc.) have been made by modelling the various experimental results using ever-more sophisticated computer programs. In this manner progressive inroads have been made into gaining a better understanding of the many components (...) of cognition. Concomitantly in both science and science fiction the hope is periodically re-ignited that a manmade system can be engineered to be fully cognitive and conscious purely in virtue of its execution of an appropriate computer program. However, whilst the usefulness of the computational metaphor in many areas of psychology and neuroscience is clear, it has not gone unchallenged and in this article I will review a group of philosophical arguments that suggest either such unequivocal optimism in computationalism is misplaced—computation is neither necessary nor sufficient for cognition—or panpsychism (the belief that the physical universe is fundamentally composed of elements each of which is conscious) is true. I conclude by highlighting an alternative metaphor for cognitive processes based on communication and interaction. (shrink)

In this book, Earl Mac Cormac presents an original and unified cognitive theory of metaphor using philosophical arguments which draw upon evidence from psychological experiments and theories. He notes that implications of this theory for meaning and truth with specific attention to metaphor as a speech act, the iconic meaning of metaphor, and the development of a four-valued system of truth. Numerous examples of metaphor from poetry and science are presented and analyzed to support Mac Cormac's (...) theory. A Cognitive Theory of Metaphortakes up three levels of explanation—metaphor as expressed in surface language, the semantics of metaphor, and metaphor as a cogitive process—and unifies these by interpreting metaphor as an evolutionary knowledge process in which metaphors mediate between minds and culture. Mac Cormac considers, and rejects, the radical theory that all use of language is metaphorical; however, this argument also recognizes that the theoryof metaphor may itself be metaphorical. The book first considers the computational metaphor often adopted by cognitive psychology as an example of metaphor requiring analysis. In contrast to three well-known philosophical theories of metaphor—the tension theory, the controversion theory, and the grammatical deviance theory—it develops a semantical anomaly theory of metaphor based on a quasi-mathematical hierarchy of words. In developing the theory, Mac Cormac makes much-needed connections between theories of metaphor and more orthodox analytic philosophy of meaning, including discussions of speech acts and the logic of fuzzy sets. This semantical theory of explanation is then shown to be compatible with contemporary psychological theories of memory. (shrink)

The metaphorical nature of biological language is examined and the use of metaphors for providing the linguistic context in which similarities and differences are made is described. Certain pervasive metaphors which are characterised by systemic properties are noted, and in order to provide some focus to the study, systemic metaphors associated with machine, text and organism are discussed. Other systemic metaphors such as society and circuit are also reported. Some details concerning interrelations between automaton and organism are presented in the (...) light of the previous discussion.An approach towards the analysis of biosystem metaphors is outlined which relates part-whole, organisational level and systemic metaphors in a single model. Examples are provided throughout the discussion and mainly come from computing. The potential for metaphorical transfers between these domains is considered. (shrink)

The Logic of Metaphor uses techniques from possible worlds semantics to provide formal truth-conditions for many grammatical classes of metaphors. It gives logically precise and practically useful syntactic and semantic rules for generating and interpreting metaphors. These rules are implemented in a working computer program. The book treats the lexicon as a conceptual network with semantics provided by an intensional predicate calculus. It gives rules for finding analogies in such networks. It shows how to syntactically and semantically analyze (...) texts containing metaphors and how to use structural similarities between parts of possible worlds to provide truth-conditions for metaphors. Meanings for metaphors are linked to the modal logics of identity and indiscernibility. The book shows how to extend deductive and abductive inference systems to handle metaphors. It shows how to handle novel metaphorical word-senses. The Logic of Metaphor will be useful to philosophers, logicians, linguists, and computer scientists. (shrink)

There seems to exist an indirect link between computer science and theology via psychology, which is founded on dualism. First, these theories from psychology, computer science and theology are considered that acknowledge the existence of (at least) two different kinds of reality, or, possibly, two different realms of the same reality. In order to express a root of incompatibility of science and theology, a distinction is drawn between ontological and epistemological dualism. It seems that computer science combines (...) ontological monism with epistemological monism, theology combines ontological and epistemological dualism, and psychologytakes a position of epistemological monism and is quite hesitant about the ontological status of the phenomena it analyzes. A direct transition from the computer metaphor to theology is almost impossible: there is no overlap of platforms between these domains. (shrink)

This book explores and offers solutions to a range of conceptual and philosophical problems that underlie attempts to understand metaphor processing in the context of cognitive science. The author vigorously criticizes the prevailing philosophical prejudice against traditional «comparison» theories of metaphor, arguing that the problems with the comparison theory are exciting problems that demand solutions, rather than grounds for rejecting the theory itself. Furthermore, it is through these problems that the study of metaphor processing is linked to (...) wider issues in cognitive science, including disputes about computational architectures and neural mechanisms. (shrink)

This text enables readers to understand human intelligence from a variety of standpoints, such as psychology, anthropology, computational science, sociology, and philosophy. Readers will gain a comprehensive understanding of the concept of intelligence and how ideas about it have evolved and are continuing to evolve. Much of the present confusion surrounding the concept of intelligence stems from our having looked at it from these different standpoints without considering how they relate to each other or how they might be combined into (...) a unified view that goes beyond the boundaries of a particular discipline. (shrink)

The terms complexity, complex adaptive systems, and sciences of complexity are found often in recent scientific literature, reflecting the remarkable growth in collaborative academic research focused on complexity from the origin and dynamics of organisms to the largest social and political organizations. One of the great challenges in this field of research is to discover which features are essential and shared by all of the seemingly disparate systems that are described as complex. Is there sufficient synthesis to suggest the possibility (...) of an overarching science of complexity? This report describes current views on this subject held by various eminent scholars associated with the Santa Fe Institute.The physical sciences have traditionally been concerned with “simple” systems whose dynamics can be described in mathematical terms with precision and certainty. In contrast, the biological and social sciences are inevitably concerned with self-organized or social “complex” systems whose detailed behaviors appear to be unpredictable. The two categories differ greatly in size and diversity, prompting the late mathematician Stanislaus Ulam to remark that research on complex systems might be compared to the study of non-elephants. Nevertheless, certain integrative themes have begun to emerge.Rising activity in this field of research runs completely counter to the trend toward increasing fragmentation and specialization in the sciences. It has stimulated a resurgence of interest in a broad synthesis involving mathematics, computational science, physics, chemistry, biology, neuroscience, and the social sciences. The growth of effort in this very extended field has been greatly stimulated by the development of new computational tools that are capable of dealing with vast, interrelated databases. Many of the participants in complexity research feel that it is now time to reintegrate the fragmented interests of much of the academic community. The reader is encouraged to consider whether such views are sparking a historic renaissance of scholarship or represent a passing scientific diversion. (shrink)

There seems to exist an indirect link between computer science and theology via psychology, which is founded on dualism. First, these theories from psychology, computer science and theology are considered that acknowledge the existence of (at least) two different kinds of reality, or, possibly, two different realms of the same reality. In order to express a root of incompatibility of science and theology, a distinction is drawn between ontological and epistemological dualism. It seems that computer science combines (...) ontological monism with epistemological monism, theology combines ontological and epistemological dualism, and psychologytakes a position of epistemological monism and is quite hesitant about the ontological status of the phenomena it analyzes. A direct transition from the computer metaphor to theology is almost impossible: there is no overlap of platforms between these domains. (shrink)

In many papers dealing with the stylistic features of legal texts, metaphor is highlighted as a stylistic figure often used in the language of law. On a daily basis we can witness the frequent use of metaphoric collocations like soft laws, hard laws, silent partner, hedge funds, etc. In this paper, the author analyses the use of denotations for colours as constituent parts of metaphoric collocations in the language of law. The analysis is conducted by using a comparative approach (...) to examples extracted by means of computer technology from international bills and conventions available online. In the main part of the paper, examples are classified by using a colour denotation as the main criterion for the classification. After that, the examples are compared with corresponding expressions used in German and Croatian. Taking into account the main principle of the Skopos translation theory that differences between cultures strongly influence the translation process, the hypothesis of this research is that in many cases there will be no lexical equivalence between collocations with colour denotation in three languages. Due to the fact that international bills and conventions build the corpus of the research, and that the English language has become the lingua franca of international communication, it can be expected that some metaphoric terms and collocations would be literally translated from English. Conclusions drawn from the comparative analysis of legal collocations containing denotations for colours can be interesting to lawyers and LSP teachers in the field of law. In this sense, results of the research can contribute to motivational aspects of teaching Legal English and Legal German. (shrink)

Some computational phenomena rely essentially on pragmatic considerations, and seem to undermine the independence of the specification from the implementation. These include software development, deviant uses, esoteric languages and recent data-driven applications. To account for them, the interaction between pragmatics, epistemology and ontology in computational artefacts seems essential, indicating the need to recover the role of the language metaphor. We propose a User Levels (ULs) structure as a pragmatic complement to the Levels of Abstraction (LoAs)-based structure defining the ontology (...) and epistemology of computational artefacts. ULs identify a flexible hierarchy in which users bear their own semantic and normative requirements, possibly competing with the logical specification. We formulate a notion of computational act intended in its pragmatic sense, alongside pragmatic versions of implementation and correctness. (shrink)

Over the past thirty years, it is been common to hear the mind likened to a digital computer. This essay is concerned with a particular philosophical view that holds that the mind literally is a digital computer (in a specific sense of “computer” to be developed), and that thought literally is a kind of computation. This view—which will be called the “Computational Theory of Mind” (CTM)—is thus to be distinguished from other and broader attempts to connect the (...) mind with computation, including (a) various enterprises at modeling features of the mind using computational modeling techniques, and (b) employing some feature or features of production-model computers (such as the stored program concept, or the distinction between hardware and software) merely as a guiding metaphor for understanding some feature of the mind. This entry is therefore concerned solely with the Computational Theory of Mind (CTM) proposed by Hilary Putnam [1961] and developed most notably for philosophers by Jerry Fodor [1975, 1980, 1987, 1993]. The senses of ‘computer’ and ‘computation’ employed here are technical; the main tasks of this entry will therefore be to elucidate: (a) the technical sense of ‘computation’ that is at issue, (b) the ways in which it is claimed to be applicable to the mind, (c) the philosophical problems this understanding of the mind is claimed to solve, and (d) the major criticisms that have accrued to this view. (shrink)

The theory that all processes in the universe are computational is attractive in its promise to provide an understandable theory of everything. I want to suggest here that this pancomputationalism is not sufficiently clear on which problem it is trying to solve, and how. I propose two interpretations of pancomputationalism as a theory: I) the world is a computer and II) the world can be described as a computer. The first implies a thesis of supervenience of the physical (...) over computation and is thus reduced ad absurdum. The second is underdetermined by the world, and thus equally unsuccessful as theory. Finally, I suggest that pancomputationalism as metaphor can be useful. – At the Paderborn workshop in 2008, this paper was presented as a commentary to the relevant paper by Gordana Dodig-Crnkovic " Info-Computationalism and Philosophical Aspects of Research in Information Sciences". (shrink)

Ever since 1956 when details of the Logic Theorist were published by Newell and Simon, a large literature has accumulated on computational models and theories of the creative process, especially in science, invention and design. But what exactly do these computational models/theories tell us about the way that humans have actually conducted acts of creation in the past? What light has computation shed on our understanding of the creative process? Addressing these questions, we put forth three propositions: (I) Computational models (...) of the creative process are fundamentally flawed as theories of human creativity. Rather, the universal power of computational models lies elsewhere: (II) Computational models of particular acts of creation can serve as effective experiments to test universal hypotheses about creative processes and mechanisms; and (III) Computation-based architectures of the creative mind provide metaphorical frameworks that, like all good metaphors, can serve as rich sources of insight into aspects of the creative process. In this paper, we provide evidence for these three propositions by drawing upon some particular episodes in the cognitive history of science, technology, and art. (shrink)