In the late summer of 1998, the authors, a cognitive scientist and a logician, started talking about the relevance of modern mathematical logic to the study of human reasoning, and we have been talking ever since. This book is an interim report of that conversation. It argues that results such as those on the Wason selection task, purportedly showing the irrelevance of formal logic to actual human reasoning, have been widely misinterpreted, mainly because the picture of logic (...) current in psychology and cognitive science is completely mistaken. We aim to give the reader a more accurate picture of mathematical logic and, in doing so, hope to show that logic, properly conceived, is still a very helpful tool in cognitive science. The main thrust of the book is therefore constructive. We give a number of examples in which logical theorizing helps in understanding and modeling observed behavior in reasoning tasks, deviations of that behavior in a psychiatric disorder (autism), and even the roots of that behavior in the evolution of the brain. (shrink)

This special issue on what some regard as a crisis of replicability in cognitive science (i.e. the observation that a worryingly large proportion of experimental results across a number of areas cannot be reliably replicated) is informed by three recent developments. -/- First, philosophers of mind and cognitive science rely increasingly on empirical research, mainly in the psychological sciences, to back up their claims. This trend has been noticeable since the 1960s (see Knobe, 2015). This development (...) has allowed philosophers to draw on a wider range of relevant resources, but it also makes them vulnerable to relying on claims that may not survive further scrutiny. If we have reasons to believe that a large proportion of findings in the psychological sciences cannot be reliably replicated, this would be a problem for philosophers who use such findings in their work. Second, philosophers are increasingly designing and carrying out their own experiments to back up claims, or to test claims earlier made from the armchair, for example, on the perceived permissibility of diverting trolleys or on the nature of free will. This growing field of experimental philosophy has diversified the intellectual field in philosophy, but may also be vulnerable to issues of replicability that philosophers did not face before. -/- Third, the recent evidence of apparently widespread non-replicability in the social sciences (and other fields) has forced philosophers of science to grapple with long standing questions from their field from a new perspective. To what extent does replicability matter for theory construction? How do the notions of replicability and scientific progress interact? How can normative insights from philosophy of science be used in order to improve scientific practice? -/- It is with these three developments in mind—the increasing importance of empirically-informed philosophy, of experimental philosophy, and of philosophy of science around replicability—that this special issue has been conceived. (shrink)

One of the classic debates in cognitive science is between nativism and empiricism about the development of psychological capacities. In principle, the debate is empirical. However, in practice nativist hypotheses have also been challenged for relying on an ill-defined, or even unscientific, notion of innateness as that which is “not learned”. Here this minimal conception of innateness is defended on four fronts. First, it is argued that the minimal conception is crucial to understanding the nativism-empiricism debate, when properly (...) construed; Second, various objections to the minimal conception—that it risks overgeneralization, lacks an account of learning, frustrates genuine explanations of psychological development, and fails to unify different notions of innateness across the sciences—are rebutted. Third, it is argued that the minimal conception avoids the shortcomings of primitivism, the prominent view that innate capacities are those that are not acquired via a psychological process in development. And fourth, the minimal conception undermines some attempts to identify innateness with a natural kind. So in short, we have little reason to reject, and good reason to accept, the minimal conception of innateness in cognitive science. (shrink)

I will present two different applications - Dual PECCS and the TCL reasoning framework - addressing some crucial aspects of commonsense reasoning (namely: dealing with typicality effects and with the problem of commonsense compositionality) in a way that is integrated or compliant with different cognitive architectures. In doing so I will show how such aspects are better dealt with at different levels of representation and will discuss the adopted solution to integrate such representational layers.

The book is addressed to all readers interested in cognitive science, and especially in research combining a logical analysis with psychological, linguistic and neurobiological approaches. The publication is the result of a collaboration between the Department of Cognitive Science at University of Lodz and the Department of Cognitive Science at Lund University. It is intended to provide a comprehensive presentation of the key research issues undertaken in both Departments, including considerations on meaning, natural language (...) and reasoning, linguistic as well as numerical competence, the theory of decision making, modelling of conceptual representations, cognitive and game theoretic approach to social interactions. (shrink)

Mental representations remain the central posits of psychology after many decades of scrutiny. However, there is no consensus about the representational format(s) of biological cognition. This paper provides a survey of evidence from computational cognitive psychology, perceptual psychology, developmental psychology, comparative psychology, and social psychology, and concludes that one type of format that routinely crops up is the language-of-thought (LoT). We outline six core properties of LoTs: (i) discrete constituents; (ii) role-filler independence; (iii) predicate–argument structure; (iv) logical operators; (v) (...) inferential promiscuity; and (vi) abstract content. These properties cluster together throughout cognitive science. Bayesian computational modeling, compositional features of object perception, complex infant and animal reasoning, and automatic, intuitive cognition in adults all implicate LoT-like structures. Instead of regarding LoT as a relic of the previous century, researchers in cognitive science and philosophy-of-mind must take seriously the explanatory breadth of LoT-based architectures. We grant that the mind may harbor many formats and architectures, including iconic and associative structures as well as deep-neural-network-like architectures. However, as computational/representational approaches to the mind continue to advance, classical compositional symbolic structures – that is, LoTs – only prove more flexible and well-supported over time. (shrink)

Using path-breaking discoveries of cognitive science, Mark Johnson argues that humans are fundamentally imaginative moral animals, challenging the view that morality is simply a system of universal laws dictated by reason. According to the Western moral tradition, we make ethical decisions by applying universal laws to concrete situations. But Johnson shows how research in cognitive science undermines this view and reveals that imagination has an essential role in ethical deliberation. Expanding his innovative studies of human reason (...) in Metaphors We Live By and The Body in the Mind, Johnson provides the tools for more practical, realistic, and constructive moral reflection. (shrink)

[from the publisher's website] Questions about the existence and attributes of God form the subject matter of natural theology, which seeks to gain knowledge of the divine by relying on reason and experience of the world. Arguments in natural theology rely largely on intuitions and inferences that seem natural to us, occurring spontaneously—at the sight of a beautiful landscape, perhaps, or in wonderment at the complexity of the cosmos—even to a nonphilosopher. In this book, Helen De Cruz and Johan De (...) Smedt examine the cognitive origins of arguments in natural theology. They find that although natural theological arguments can be very sophisticated, they are rooted in everyday intuitions about purpose, causation, agency, and morality. Using evidence and theories from disciplines including the cognitive science of religion, evolutionary ethics, evolutionary aesthetics, and the cognitive science of testimony, they show that these intuitions emerge early in development and are a stable part of human cognition. -/- De Cruz and De Smedt analyze the cognitive underpinnings of five well-known arguments for the existence of God: the argument from design, the cosmological argument, the moral argument, the argument from beauty, and the argument from miracles. Finally, they consider whether the cognitive origins of these natural theological arguments should affect their rationality. (shrink)

Philosophers of mind commonly draw a distinction between the personal level – the distinctive realm of conscious experience and reasoned deliberation – and the subpersonal level, the domain of mindless mechanism and brute cause and effect. Moreover, they tend to view cognitive science through the lens of this distinction. Facts about the personal level are given a priori, by introspection, or by common sense; the job of cognitive science is merely to investigate the mechanistic basis of (...) these facts. I argue that this view misrepresents the structure of cognitive-scientific enquiry. Taken at face value, cognitive science makes no commitment to the existence of a distinctive level at which persons or selves appear. Thus, in the age of cognitive science, we should not expect to find the self in an ontologically distinct realm. Instead, we should expect to locate it in cognitive-scientific models themselves. In closing, I indicate likely results of this approach. (shrink)

This paper outlines the case for a future research program that uses the tools of experimental cognitive science to investigate questions that traditionally fall under the remit of the philosophy of historiography. The central idea is this – the epistemic profile of historians’ representations of the past is largely an empirical matter, determined in no small part by the cognitive processes that produce these representations. However, as the philosophy of historiography is not presently equipped to investigate such (...) cognitive questions, legitimate concerns about evidential quality go largely overlooked. The case of mental state representation provides an excellent illustration of this. Representations of past mental states – the thoughts and fears and knowledge and desires of past agents – play much the same evidential role in historiography as in everyday life, serving in the causal explanation of agents’ behaviors and supporting normative evaluation of those behaviors. However, we have good reason to suspect that the theory of mind processes that support these representations may be more susceptible to error when deployed in the context of historiography than under everyday conditions. This raises worries about the quality of evidence that theory of mind can provide historiography, worries which require experimental cognitive science to properly address. (shrink)

The paper presents the heterogeneous proxytypes hypothesis as a cognitively-inspired computational framework able to reconcile, in both natural and artificial systems, different theories of typicality about conceptual representation and reasoning that have been traditionally seen as incompatible. In particular, through the Dual PECCS system and its evolution, it shows how prototypes, exemplars and theory-theory like conceptual representations can be integrated in a cognitive artificial agent (thus extending its categorization capabilities) and, in addition, can provide useful insights in the (...) context of a computationally grounded science of the mind. (shrink)

Commonsense reasoning is one of the main open problems in the field of Artificial Intelligence (AI) while, on the other hand, seems to be a very intuitive and default reasoning mode in humans and other animals. In this talk, we discuss the different paradigms that have been developed in AI and Computational Cognitive Science to deal with this problem (ranging from logic-based methods, to diagrammatic-based ones). In particular, we discuss - via two different case studies concerning (...) commonsense categorization and knowledge invention tasks - how cognitively inspired heuristics can help (both in terms of efficiency and efficacy) in the realization of intelligent artificial systems able to reason in a human-like fashion, with results comparable to human-level performances. (shrink)

Within contemporary science, it is common practice to compare data points to the average, i.e., to the statistical mean. Because this practice is so familiar, it might at first appear not to be the sort of thing that requires explanation. But recent research in cognitive science and in the history of science gives us reason to adopt the opposite perspective. Cognitive science research on the ways people ordinarily make sense of the world suggests that, (...) instead of using a purely statistical notion of the average, people tend to use a value-laden notion of the normal. Similarly, historical research on the scientific practices used in other time periods indicates that, prior to the nineteenth century, scientists tended to make use of a notion of the normal that was overtly value-laden. These findings give us reason to rethink certain familiar facts about scientific practice. In particular, they suggest that the fact that scientists so often make use of the statistical average should be seen as a highly surprising fact, the sort of thing that calls out for explanation. (shrink)

Endowing artificial systems with explanatory capacities about the reasons guiding their decisions, represents a crucial challenge and research objective in the current fields of Artificial Intelligence (AI) and Computational Cognitive Science [Langley et al., 2017]. Current mainstream AI systems, in fact, despite the enormous progresses reached in specific tasks, mostly fail to provide a transparent account of the reasons determining their behavior (both in cases of a successful or unsuccessful output). This is due to the fact that the (...) classical problem of opacity in artificial neural networks (ANNs) explodes with the adoption of current Deep Learning techniques [LeCun, Bengio, Hinton, 2015]. In this paper we argue that the explanatory deficit of such techniques represents an important problem, that limits their adoption in the cognitive modelling and computational cognitive science arena. In particular we will show how the current attempts of providing explanations of the deep nets behaviour (see e.g. [Ritter et al. 2017] are not satisfactory. As a possibile way out to this problem, we present two different research strategies. The first strategy aims at dealing with the opacity problem by providing a more abstract interpretation of neural mechanisms and representations. This approach is adopted, for example, by the biologically inspired SPAUN architecture [Eliasmith et al., 2012] and by other proposals suggesting, for example, the interpretation of neural networks in terms of the Conceptual Spaces framework [Gärdenfors 2000, Lieto, Chella and Frixione, 2017]. All such proposals presuppose that the neural level of representation can be considered somehow irrelevant for attacking the problem of explanation [Lieto, Lebiere and Oltramari, 2017]. In our opinion, pursuing this research direction can still preserve the use of deep learning techniques in artificial cognitive models provided that novel and additional results in terms of “transparency” are obtained. The second strategy is somehow at odds with respect to the previous one and tries to address the explanatory issue by avoiding to directly solve the “opacity” problem. In this case, the idea is that one of resorting to pre-compiled plausible explanatory models of the word used in combination with deep-nets (see e.g. [Augello et al. 2017]). We argue that this research agenda, even if does not directly fits the explanatory needs of Computational Cognitive Science, can still be useful to provide results in the area of applied AI aiming at shedding light on the models of interaction between low level and high level tasks (e.g. between perceptual categorization and explanantion) in artificial systems. (shrink)

In this article, I discuss what motivated reasoning research tells us about the prospects for deliberative democracy. In section I, I introduce the results of several political psychology studies examining the problematic affective and cognitive processing of political information by individuals in nondeliberative, experimental environments. This is useful because these studies are often neglected in political philosophy literature. Section II has three stages. First, I sketch how the study results from section I question the practical viability of deliberative (...) democracy. Second, I briefly present the results of three empirical studies of political deliberation that can be interpreted to counter the findings of the studies in section I. Third, I show why this is a misinterpretation and that the study results from section I mean that it is implausible that sites of political deliberation would naturally emerge from the wide public sphere and coalesce into institutionalized forms of the practice such that deliberative democracy can satisfy its raison d’être. Finally, in section III, I conclude that viable conceptions of deliberative democracy should be limited to narrower aims. (shrink)

Religious belief and behavior raises the following two questions: (Q1) Does God, or any other being or state that is integral to various religious traditions, exist? (Q2) Why do humans have religious beliefs and engage in religious behavior? How one answers (Q2) can affect how reasonable individuals can be in accepting a particular answer to (Q1). My aim in this chapter is to carefully distinguish the various ways in which an answer to Q2 might affect the rationality of believing in (...) God. A literature has sprouted around this exact issue, but it has heretofore focused almost exclusively on one way in which a genealogy for p can affect the rationality of believing p – namely, by the genealogy functioning within a debunking argument. However, there are other ways a genealogy can affect the rationality of a belief. I suggest that we should be interested in whether genealogies more broadly cast doubt on religious beliefs. My main goal is: (i) to argue that CSR does not cast doubt on theistic belief in a few of the primary ways that propositions can cast doubt on other propositions, including via a debunking argument; and (ii) to suggest that one plausible way in which CSR might cast doubt on theistic belief is by undermining various traditional theistic reasons, and to illustrate how this might work with one example of a traditional theistic reason – religious experience. (shrink)

A collection of papers presented at the First International Summer Institute in Cognitive Science, University at Buffalo, July 1994, including the following papers: ** Topological Foundations of Cognitive Science, Barry Smith ** The Bounds of Axiomatisation, Graham White ** Rethinking Boundaries, Wojciech Zelaniec ** Sheaf Mereology and Space Cognition, Jean Petitot ** A Mereotopological Definition of 'Point', Carola Eschenbach ** Discreteness, Finiteness, and the Structure of Topological Spaces, Christopher Habel ** Mass Reference and the Geometry of (...) Solids, Almerindo E. Ojeda ** Defining a 'Doughnut' Made Difficult, N .M. Gotts ** A Theory of Spatial Regions with Indeterminate Boundaries, A.G. Cohn and N.M. Gotts ** Mereotopological Construction of Time from Events, Fabio Pianesi and Achille C. Varzi ** Computational Mereology: A Study of Part-of Relations for Multi-media Indexing, Wlodek Zadrozny and Michelle Kim. (shrink)

Hume was a cognitive scientist of religion avant la lettre. His Natural History of Religion (1757 [2007]) locates the origins of religion in human nature. This paper explores similarities between some of his ideas and the cognitive science of religion, the multidisciplinary study of the psychological origins of religious beliefs. It also considers Hume’s distinction between two questions about religion: its foundation in reason (the domain of natural theology and philosophy of religion) and its origin in human (...) nature (the domain of cognitive science of religion). (shrink)

How can we think about things in the outside world? There is still no widely accepted theory of how mental representations get their meaning. In light of pioneering research, Nicholas Shea develops a naturalistic account of the nature of mental representation with a firm focus on the subpersonal representations that pervade the cognitive sciences.

This paper evaluates the Natural-Kinds Argument for cognitive extension, which purports to show that the kinds presupposed by our best cognitive science have instances external to human organism. Various interpretations of the argument are articulated and evaluated, using the overarching categories of memory and cognition as test cases. Particular emphasis is placed on criteria for the scientific legitimacy of generic kinds, that is, kinds characterized in very broad terms rather than in terms of their fine-grained causal roles. (...) Given the current state of cognitive science, I conclude that we have no reason to think memory or cognition are generic natural kinds that can ground an argument for cognitive extension. (shrink)

Regard for Reason in the Moral Mind argues that a careful examination of the scientific literature reveals a foundational role for reasoning in moral thought and action. Grounding moral psychology in reason then paves the way for a defense of moral knowledge and virtue against a variety of empirical challenges, such as debunking arguments and situationist critiques. The book attempts to provide a corrective to current trends in moral psychology, which celebrate emotion over reason and generate pessimism about the (...) psychological mechanisms underlying commonsense morality. Ultimately, there is rationality in ethics not just despite but in virtue of the neurobiological and evolutionary materials that shape moral cognition and motivation. (shrink)

Common sense is on the one hand a certain set of processes of natural cognition - of speaking, reasoning, seeing, and so on. On the other hand common sense is a system of beliefs (of folk physics, folk psychology and so on). Over against both of these is the world of common sense, the world of objects to which the processes of natural cognition and the corresponding belief-contents standardly relate. What are the structures of this world? How does the (...) scientific treatment of this world relate to traditional and contemporary metaphysics and formal ontology? Can we embrace a thesis of common-sense realism to the effect that the world of common sense exists uniquely? Or must we adopt instead a position of cultural relativism which would assign distinct worlds of common sense to each group and epoch? The present paper draws on recent work in computer science (especially in the fields of naive and qualitative physics), in perceptual and developmental psychology, and in cognitive anthropology, in order to consider in a new light these and related questions and to draw conclusions for the methodology and philosophical foundations of the cognitive sciences. (shrink)

We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.

In this article I consider the relevance of Tomasello’s work on social cognition to the theory of communicative action. I argue that some revisions are needed to cope with Tomasello’s results, but they do not affect the core of the theory. Moreover, they arguably reinforce both its explanatory power and the plausibility of its normative claims. I proceed in three steps. First, I compare and contrast Tomasello’s views on the ontogeny of human social cognition with the main tenets of Habermas’ (...) theory of communicative action. Second, I suggest how to reframe the role of language in the theory of communicative rationality in order to integrate the two theories. Third, I show how this affects social ontology, supporting the view that the construction of social reality is normatively constrained by the bounds of reason. (shrink)

The mainstream view in cognitive science is that computation lies at the basis of and explains cognition. Our analysis reveals that there is no compelling evidence or argument for thinking that brains compute. It makes the case for inverting the explanatory order proposed by the computational basis of cognition thesis. We give reasons to reverse the polarity of standard thinking on this topic, and ask how it is possible that computation, natural and artificial, might be based on cognition (...) and not the other way around. (shrink)

Resource rationality may explain suboptimal patterns of reasoning; but what of “anti-Bayesian” effects where the mind updates in a direction opposite the one it should? We present two phenomena — belief polarization and the size-weight illusion — that are not obviously explained by performance- or resource-based constraints, nor by the authors’ brief discussion of reference repulsion. Can resource rationality accommodate them?

This article addresses an open problem in the area of cognitive systems and architectures: namely the problem of handling (in terms of processing and reasoning capabilities) complex knowledge structures that can be at least plausibly comparable, both in terms of size and of typology of the encoded information, to the knowledge that humans process daily for executing everyday activities. Handling a huge amount of knowledge, and selectively retrieve it according to the needs emerging in different situational scenarios, is (...) an important aspect of human intelligence. For this task, in fact, humans adopt a wide range of heuristics (Gigerenzer & Todd) due to their “bounded rationality” (Simon, 1957). In this perspective, one of the requirements that should be considered for the design, the realization and the evaluation of intelligent cognitively-inspired systems should be rep- resented by their ability of heuristically identify and retrieve, from the general knowledge stored in their artificial Long Term Memory (LTM), that one which is synthetically and contextually relevant. This requirement, however, is often neglected. Currently, artificial cognitive systems and architectures are not able, de facto, to deal with complex knowledge structures that can be even slightly comparable to the knowledge heuris- tically managed by humans. In this paper I will argue that this is not only a technological problem but also an epistemological one and I will briefly sketch a proposal for a possible solution. (shrink)

Starting with 1985, we discovered the possible existence of electrons with net helicity in biomolecules as amino acids and their possibility to discern between the two quantum spin states. It is well known that the question of a possible fundamental role of quantum mechanics in biological matter constitutes still a long debate. In the last ten years we have given a rather complete quantum mechanical elaboration entirely based on Clifford algebra whose basic entities are isomorphic to the well known spin (...) Pauli matrices. A number of our recent results indicate the possible logical origin of quantum mechanics and the direct admission of quantum mechanics in the field of cognitive sciences. In February 2011 the authors Gölder et al., published their important discovery on Science about Spin Selectivity in Electron Transmission Through Self-Assembled Monolayers of Double-Stranded DNA confirming in such manner that the principles of quantum mechanics apply to biological systems. (shrink)

This brief commentary has three goals. The first is to argue that ‘‘framework debate’’ in cognitive science is unresolvable. The idea that one theory or framework can singly account for the vast complexity and variety of cognitive processes seems unlikely if not impossible. The second goal is a consequence of this: We should consider how the various theories on offer work together in diverse contexts of investigation. A final goal is to supply a brief review for readers (...) who are compelled by these points to explore existing literature on the topic. Despite this literature, pluralism has garnered very little attention from broader cognitive science. We end by briefly considering what it might mean for theoretical cognitive science. (shrink)

This dissertation argues that cognition is a kind of natural agency. Natural agency is the capacity that certain systems have to act in accordance with their own norms. Natural agents are systems that bias their repertoires in response to affordances in the pursuit of their goals. -/- Cognition is a special mode of this general phenomenon. Cognitive systems are agents that have the additional capacity to actively take their worlds to be certain ways, regardless of whether the world is (...) really that way. In this way, cognitive systems are desituated. Desituatedness is the root of specifically cognitive capacities for representation and abstraction. -/- There are two main reasons why this view needs defending. First, natural agency is typically viewed as incompatible with natural science because it is committed to a teleological mode of explanation. Second, cognition is typically held to be categorically distinct from natural agency. This dissertation argues against both of these views. It argues against the incompatibility of agency and natural science by demonstrating that systems biology, general systems theory, and sciences that deal with complex systems have typically underappreciated conceptual and theoretical resources for grounding agency in the causal structure of the world. These conceptual resources do not, however, reduce agency to systems theory because the normativity inherent in agency demands descriptive resources beyond those of even the most sophisticated systems theory. It argues against the categorical difference between natural agency and cognition by pointing out that separating cognition from a richer web of situated, ecologically embedded relations between the agent and the world generates the frame problem, which is an insuperable obstacle to making cognition that is sufficiently responsive to the complexity of the world. Rooting cognition in natural agency is a more robust empirical bet for theorizing cognition and artificial intelligence. (shrink)

This dissertation argues that cognition is a kind of natural agency. Natural agency is the capacity that certain systems have to act in accordance with their own norms. Natural agents are systems that bias their repertoires in response to affordances in the pursuit of their goals. Cognition is a special mode of this general phenomenon. Cognitive systems are agents that have the additional capacity to actively take their worlds to be certain ways, regardless of whether the world is really (...) that way. In this way, cognitive systems are desituated. Desituatedness is the root of specifically cognitive capacities for representation and abstraction. There are two main reasons why this view needs defending. First, natural agency is typically viewed as incompatible with natural science because it is committed to a teleological mode of explanation. Second, cognition is typically held to be categorically distinct from natural agency. This dissertation argues against both of these views. It argues against the incompatibility of agency and natural science by demonstrating that systems biology, general systems theory, and sciences that deal with complex systems have typically underappreciated conceptual and theoretical resources for grounding agency in the causal structure of the world. These conceptual resources do not, however, reduce agency to systems theory because the normativity inherent in agency demands descriptive resources beyond those of even the most sophisticated systems theory. It argues against the categorical difference between natural agency and cognition by pointing out that separating cognition from a richer web of situated, ecologically embedded relations between the agent and the world generates the frame problem, which is an insuperable obstacle to making cognition that is sufficiently responsive to the complexity of the world. Rooting cognition in natural agency is a more robust empirical bet for theorizing cognition and artificial intelligence. (shrink)

In the philosophy of science, it is a common proposal that values are illegitimate in science and should be counteracted whenever they drive inquiry to the confirmation of predetermined conclusions. Drawing on recent cognitive scientific research on human reasoning and confirmation bias, I argue that this view should be rejected. Advocates of it have overlooked that values that drive inquiry to the confirmation of predetermined conclusions can contribute to the reliability of scientific inquiry at the group (...) level even when they negatively affect an individual’s cognition. This casts doubt on the proposal that such values should always be illegitimate in science. It also suggests that advocates of that proposal assume a narrow, individualistic account of science that threatens to undermine their own project of ensuring reliable belief formation in science. (shrink)

Cognitive science is an interdisciplinary conglomerate of various research fields and disciplines, which increases the risk of fragmentation of cognitive theories. However, while most previous work has focused on theoretical integration, some kinds of integration may turn out to be monstrous, or result in superficially lumped and unrelated bodies of knowledge. In this paper, I distinguish theoretical integration from theoretical unification, and propose some analyses of theoretical unification dimensions. Moreover, two research strategies that are supposed to lead (...) to unification are analyzed in terms of the mechanistic account of explanation. Finally, I argue that theoretical unification is not an absolute requirement from the mechanistic perspective, and that strategies aiming at unification may be premature in fields where there are multiple conflicting explanatory models. (shrink)

A recurring claim in a number of behavioural, cognitive and neuro-scientific literatures is that there is, or must be, a unidimensional ‘common currency’ in which the values of different available options are represented. There is striking variety in the quantities or properties that have been proposed as determinants of the ordering in motivational strength. Among those seriously suggested are pain and pleasure, biological fitness, reward and reinforcement, and utility among economists, who have regimented the notion of utility in a (...) variety of ways, some of them incompatible. This topic deserves philosophical attention for at least the following reasons. Repeated invocation of the ‘common currency’ idiom isn’t merely terminological coincidence because most of the claims are competing explanations either of manifest pattern in choices, or of order in the processes producing choice. We can’t suppose that the different currency claims within each area are compatible, because there are significant obstacles to identifying pairs of members of either the ‘pattern’ or ‘process’ group. There are, finally, seriously opposed positions about the relationships between the pattern facts and the process facts. There are philosophical positions both favouring and opposing a common currency. But direct consideration of the abstract relationships between claims about common currencies across scientific settings, and the arguments for and against these claims, is relatively rare. There is, though, much of philosophical interest to be found here. (shrink)

In this paper, we defend a novel, multidimensional account of representational unification, which we distinguish from integration. The dimensions of unity are simplicity, generality and scope, non-monstrosity, and systematization. In our account, unification is a graded property. The account is used to investigate the issue of how research traditions contribute to representational unification, focusing on embodied cognition in cognitive science. Embodied cognition contributes to unification even if it fails to offer a grand unification of cognitive science. (...) The study of this failure shows that unification, contrary to what defenders of mechanistic explanation claim, is an important mechanistic virtue of research traditions. (shrink)

A central component of the cognitive revolution is a commitment to explaining behaviour by reference to internal representations of the world. This core aspect.

Bayesian models can be related to cognitive processes in a variety of ways that can be usefully understood in terms of Marr's distinction among three levels of explanation: computational, algorithmic and implementation. In this note, we discuss how an integrated probabilistic account of the different levels of explanation in cognitive science is resulting, at least for the current research practice, in a sort of unpredicted epistemological shift with respect to Marr's original proposal.

In his rich and provocative paper, Peter Carruthers announces two related theses: (a) a positive thesis that “central cognition is sensory based, depending on the activation and deployment of sensory images of various sorts” (Carruthers 2013) and (b) a negative thesis that the “central mind does not contain any workspace within which goals, decisions, intentions, or non-sensory judgments can be active” (Carruthers 2013). These are striking claims suggesting that a natural view about cognition, namely that explicit theoretical reasoning involves (...) direct operations over beliefs, is wrong. Our beliefs, on this natural view, interact with each other to yield new beliefs. If Carruthers is right, beliefs have only an indirect or mediated influence in cognition with sensory states playing the direct role. I think it an important feature of Carruthers’ discussion that he draws support from work on the neural circuits and mechanisms that subserve these processes. In what follows, I want to regis. (shrink)

This paper examines the cognitive foundations of natural theology: the intuitions that provide the raw materials for religious arguments, and the social context in which they are defended or challenged. We show that the premises on which natural theological arguments are based rely on intuitions that emerge early in development, and that underlie our expectations for everyday situations, e.g., about how causation works, or how design is recognized. In spite of the universality of these intuitions, the cogency of natural (...) theological arguments remains a matter of continued debate. To understand why they are controversial, we draw on social theories of reasoning and argumentation. (shrink)

I discuss whether there are some lessons for philosophical inquiry over the nature of simulation to be learnt from the practical methodology of reengineering. I will argue that reengineering serves a similar purpose as simulations in theoretical science such as computational neuroscience or neurorobotics, and that the procedures and heuristics of reengineering help to develop solutions to outstanding problems of simulation.

This paper challenges the first Gettier counterexample to the tripartite account of knowledge. Noting that 'the man who will get the job' is a description and invoking Donnellan's distinction between their 'referential' and 'attributive' uses, I argue that Smith does not actually believe that the man who will get the job has ten coins in his pocket. Smith's ignorance about who will get the job shows that the belief cannot be understood referentially, his ignorance of the coins in his pocket (...) shows that it cannot be understood attributively. An explanation for why Smith appeared to have justified true belief is given by distinguishing between 'belief' and 'belief in truth'. Smith believes the sentence 'the man who will get the job has ten coins in his pocket' to be true (he mistakenly believes that Jones will get the job, of whom he knows that he has ten coins in his pocket) (hence his 'belief'), the sentence is true (hence 'truth'), and he has sufficient reason to assent to it (hence his 'justification'). But he does not believe the proposition expressed. Hence he does not know it either. (shrink)

Functional reductionism concerning mental properties has recently been advocated by Jaegwon Kim in order to solve the problem of the 'causal exclusion' of the mental. Adopting a reductionist strategy first proposed by David Lewis, he regards psychological properties as being 'higher-order' properties functionally defined over 'lower-order' properties, which are causally efficacious. Though functional reductionism is compatible with the multiple realizability of psychological properties, it is blocked if psychological properties are subdivided or crosscut by neurophysiological properties. I argue that there is (...) recent evidence from cognitive neuroscience that shows that this is the case for the psychological property of fear. Though this may suggest that some psychological properties should be revised in order to conform to those of neurophysiology, the history of science demonstrates that this is not always the outcome, particularly with properties that play an important role in our folk theories and are central to human concerns. (shrink)

In this article, I show the role that the philosopher of cognitive science can cur-rently play in cognitive science research. I argue for the important, and not yet considered, role of the philosophy of cognitive science in cognitive science, that is, the importance of cooperation between philosophers of science with cogni-tive scientists in investigating the research methods and theoretical assump-tions of cognitive science. At the beginning of the paper I (...) point out, how the philosopher of science, here, the philosopher of cognitive science, can participate in interdisciplinary research. I am opting of the cooperation in investigating the so-called reflective problems. Then, I discuss four examples of issues important for the cognitive science, in which the competences possessed by the philosopher are useful. At the ending I point out wider landscape of possible cooperation of philosophers with cognitive scientists. (shrink)

Many models of cognitive ability and disability rely on the idea of cognition as abstract reasoning processes implemented in the brain. Research in cognitive science, however, emphasizes the way that our cognitive skills are embodied in our more basic capacities for sensing and moving, and the way that tools in the external environment can extend the cognitive abilities of our brains. This chapter addresses the implications of research in embodied cognition and extended cognition for (...) how we think about cognitive impairment and rehabilitation, how cognitive reserve mitigates neural impairment, and the distinction between medical and social models of disability. (shrink)

Experts in Artificial Intelligence (AI) development predict that advances in the dvelopment of intelligent systems and agents will reshape vital areas in our society. Nevertheless, if such an advance isn't done with prudence, it can result in negative outcomes for humanity. For this reason, several researchers in the area are trying to develop a robust, beneficial, and safe concept of artificial intelligence. Currently, several of the open problems in the field of AI research arise from the difficulty of avoiding unwanted (...) behaviors of intelligent agents, and at the same time specifying what we want such systems to do. It is of utmost importance that artificial intelligent agents have their values aligned with human values, given the fact that we cannot expect an AI to develop our moral preferences simply because of its intelligence, as discussed in the Orthogonality Thesis. Perhaps this difficulty comes from the way we are addressing the problem of expressing objectives, values, and ends, using representational cognitive methods. A solution to this problem would be the dynamic cognitive approach proposed by Dreyfus, whose phenomenological philosophy defends that the human experience of being-in-the-world cannot be represented by the symbolic or connectionist cognitive methods. A possible approach to this problem would be to use theoretical models such as SED (situated embodied dynamics) to address the values learning problem in AI. (shrink)

A science of metaphysics adhering to Immanuel Kant's critical demands as set forth in his "Critique of Pure Reason", and "Prolegomena to Any Future Metaphysic...." The work includes an Appendix that quotes Kant's most relevant remarks in this regard, along with his criterion for objective validity that, given the technical jargon, can be next to impossible to interpret even for those most familiar with Kant. The Appendix allows Kant to interpret himself, the point being that many secondary works enter (...) into conflict with Kant. This can be seen most notably with respect to the somewhat understandable notion that Kant was opposed to speculative metaphysics; but Kant's criterion for objective validity undermines this closed-to-speculative-metaphysics interpretation. As a science in the Kantian sense this work (in this latest edition there is a 2/3 page abstract diagram of the science that makes it more conceptually clear) offers an opportunity for those inclinec to shy away from speculative metaphysics to reexamine their interpretations, for as yet there is just as Kant states, no such thing as metaphysics, aside from such a science (Hegel notwithstanding). The objectives are as Kant mentions in the introduction to his CPR: God, Freedom, and Immortality; and that these problems can be dealt with rationally can be seen in this work; and without fear of violating Kant's reasonable and justifiable strictures, the main one being that where anything offered in the name of pure reason is concerned, it must be such that it helps us to make sense of our phenomenal world. And as to Kant's prerequisite test: "How are synthetic cognitions, a priori possible?" I refer only to my essay "Beyond Kant and Hegel (In Answer to the Question ...)" ... in "The Review of Metaphysics", March 2013. The premise advanced in the essay may be seen to be fully apparent in this science of metaphysics. (shrink)

This chapter examines the pragmatist approach to cognition and experience and provides some of the conceptual background to the “pragmatic turn” currently underway in cognitive science. Classical pragmatists wrote extensively on cognition from a naturalistic perspective, and many of their views are compatible with contemporary pragmatist approaches such as enactivist, extended, and embodied-Bayesian approaches to cognition. Three principles of a pragmatic approach to cognition frame the discussion: First, thinking is structured by the interaction of an organism with its (...) environment. Second, cognition develops via exploratory inference, which remains a core cognitive ability throughout the life cycle. Finally, inquiry/problem solving begins with genuinely irritating doubts that arise in a situation and is carried out by exploratory inference. (shrink)

This paper considers the question of whether the influential distinction between levels of explanation introduced by David Marr can be used as a general framework for contemplating levels of explanation in cognitive sciences. Marr introduced three levels at which we can explain cognitive processes: the computational, algorithmic, and implementational levels. Some argue that Marr’s levels of explanation can only be applied to modular cognitive systems. However, since many psychological processes are non-modular, it seems that Marr’s levels of (...) explanation cannot explain such psychological processes. To show that the latter claim is not convincing, the paper draws upon an influential paradigm from cognitive sciences that is based on the principle of free energy. Based on this paradigm, the paper argues that even non-modular psychological processes can be computationally analyzed and algorithmically implemented. The conclusion of the paper is that, at least under the assumption that the func- tion of the mind is to minimize free energy, Marr’s levels of explanation can be successfully used as a general framework for understanding psychological processes at different levels of description. (shrink)

Nicholas Shea offers Varitel Semantics as a naturalistic account of mental content. I argue that the account secures determinate content only by appeal to pragmatic considerations, and so it fails to respect naturalism. But that is fine, because representational content is not, strictly speaking, necessary for explanation in cognitive science. Even in Shea’s own account, content serves only a variety of heuristic functions.