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)

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)

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.

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)

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)

[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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

Representational and embodied approaches to cognitive science are often presented in opposition to one another, with Merleau-Ponty serving as a historical precursor to embodied approaches. We argue that the two approaches are compatible and complementary, and that both can be used to interpret Merleau-Ponty's (and Husserl's) work. To support our arguments, we describe two forms of representation associated with two distinct processes. Motor intentionality is a process of direct embodied interaction (reflexes, habits, skilled behaviors) which use mediating representations (...) to bind sensory information together and guide behavior. These internal states reliably indicate specific stimuli (even if just during a transient episode), are associated with a determinate phenomenal character (a “typical physiognomy”), and correspond to what Husserl describes as passive synthesis. Higher-level processes like reasoning make use of more explicit representations (what Husserl calls active processes), which are associated with focused attention and “explicated” propositional contents. The two kinds of process can occur independently, but are often fully woven together, as for example when a friend makes explicit suggestions while the two of you cook. We also discuss Merleau-Ponty’s famous Schneider case, which makes vivid what happens when both types of processes (motor intentionality and high-level reasoning; passive and active synthesis) are intact, but when some explicit representations are damaged. A certain stratum of virtual or projected space is lost, and so a certain kind of abstractly guided behavior is unavailable to him. (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 discuss and demonstrate how research into real‐world scientific problem‐solving provides a novel window on the mind and insight into the human capacity to design and utilize resource rich environments at the highly creative end of the cognitive spectrum.

Some ethicists try to settle moral disagreement by ruling out particular types of moral reasoning on the basis of cognitive scientific evidence. We argue that the cognitive science of reasoning is not well-suited to this Archimedean role. Through discussion of several influential research programs, we show that such attempts tend to either fail to be Archimedean (by assuming controversial moral views) or fail to settle disagreement (by getting caught up in unsettled debates about rationality). We (...) speculate that these outcomes reflect a fundamental sort of normative disagreement, which can be reshuffled to the domains of morality or rationality, but cannot be avoided. (shrink)

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)

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)

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)

In humans, at least some of our ability to coordinate our actions with the timing of events in our world is due to our capacities for temporal cognition. However, controversy arises when we turn our attention to the animal world. In this paper, we will argue that apes, especially Taï Chimpanzees, are capable of genuine temporal cognition. That is, they are able to mentally represent and reason about time in cognition. We do this by developing a novel analysis of the (...) mental representation of time. (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.

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)

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 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)

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 dissertation is about the relationship between Epistemology and other domains. In it I want to show that in an important sense, Epistemology is an autonomous domain. That is, epistemic vocabulary (e.g., “knowledge”, “justification”, “rationality”, “epistemic reason”, etc.) cannot be analyzed without remainder into non-epistemic vocabulary. Epistemic phenomena must be explained in terms of epistemic reasons and the form of assessment proprietary to them. Although epistemic vocabulary cannot be reduced to the vocabulary of other domains, Epistemology is nonetheless connected with (...) other domains in an important way. In this dissertation I focus on the connection between Epistemology and the Philosophy of Mind. I distinguish different forms cognitive self-monitoring can take and corresponding forms of cognitive autonomy. The kind of self-monitoring that receives the most attention involves simulating interpersonal argumentation. I argue that the capacity to self-monitor in this way grounds familiar epistemic standards (e.g., knowledge and justification) and explains how reasons get their grip on us. On the picture that emerges, Epistemology and Philosophy of Mind need to be done in tandem. Epistemology gives us the normative framework that is modeled by the self-monitoring system. The self-monitoring system, conversely, explains the kind of activity we engage in that makes that normative framework applicable to us. Epistemic reasons themselves are just episodes of this kind of activity. In Chapter 1 I argue that epistemic luck cannot be analyzed in non-epistemic terms. Here I generalize Jennifer Lackey’s criticism of Duncan Pritchard’s safety-based account of epistemic luck to all reductive theories. I argue that they will either be extensionally inadequate, or they will illicitly presuppose the vocabulary they are trying to reduce. The upshot is that epistemic luck can only be understood in terms of the epistemic assessment of reasons. By extension, we can’t give a reductive analysis of knowledge. This is not to say we cannot analyze knowledge, just that we can’t analyze away the epistemic vocabulary without remainder. In chapter 2 I explain the relation between epistemic luck, epistemic justification, and knowledge. I argue that previous work in the defeasible reasoning tradition, despite being on the right track, fell short of realizing its full potential. This is because the account of how these three things relate given by its proponents was insufficiently unified, which encouraged many epistemologists to abandon the defeasible reasoning tradition entirely. I argue that a unified and principled account of their relation is possible, and it allows for an elegant analysis of knowledge. In slogan form: good reasons are apparent to the knowing subject. In chapter 3 I extend the defeasible reasoning tradition to explain how knowledge is gradable. I show that this enables us to bring the debates about fake barns and knowledge from falsehoods to ecumenical resolutions, while also shedding light on a new kind of case. Furthermore, I explain how background assumptions are themselves defeasible and some of the epistemic significance of this fact. In chapter 4 I make the connection between Epistemology and Philosophy of Mind. I argue that the self-monitoring system of cognitively mature humans uses a model of the normative framework described in the previous chapters to regulate its own cognition. Here I build on that claim to develop an account of the role played by knowledge and justification in doxastic social coordination. I build on the claim that background assumptions are themselves defeasible to develop an account of the foundations of knowledge according to which they are social but not brutely sociological. In chapter 5 I discuss the relation between the epistemic states of cognitively mature humans, children, and non-human animals. I do this in a way meant to integrate an insight from virtue epistemology into the reasons-first picture developed here: positive epistemic standing is a state attributable to the subject. In chapter 6 I discuss the metaphysics of epistemic reasons. I claim that they are episodes of the activity of reasoning. In the preceding chapters, we get a sense of what that activity involves. Here I argue that the materials developed there put us in a position to understand what epistemic reasons are. This account incorporates the insights of rival positions while sidestepping familiar objections to them. The resulting picture is in line with the non-reductive approach to the epistemic developed so far. In fact, it goes further than other “reasons-first” approaches to Epistemology by claiming that reasons are not only basic within Epistemology, but they are also basic full-stop. One key consideration for my argument here is that reasons are, by their very nature, competitors. Although this point is generally acknowledged in the literature on reasons, its consequences for the metaphysics of reasons hasn’t been. Participants in the debate about the metaphysics of reasons typically try to identify reasons with something (e.g., facts or mental states) that are either not competitors, or only competitors insofar as they constitute, or bear on the epistemic assessment of, episodes of reasoning. (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)

The arguments of Fodor, Garret, Walker and Parkes [(1980) Against definitions, Cognition, 8, 263-367] are the source of widespread skepticism in cognitive science about lexical semantic structure. Whereas the thesis that lexical items, and the concepts they express, have decompositional structure (i.e. have significant constituents) was at one time "one of those ideas that hardly anybody [in the cognitive sciences] ever considers giving up" (p. 264), most researchers now believe that "[a]ll the evidence suggests that the classical (...) [(decompositional)] view is wrong as a general theory of concepts" [Smith, Medin & Rips (1984) A psychological approach to concepts: comments on Rey, Cognition, 17, 272], and cite Fodor et al. (1980) as "sounding the death knell for decompositional theories" [MacNamara & Miller (1989) Attributes of theories of meaning, Psychological Bulletin, 106, 360]. I argue that the prevailing skepticism is unmotivated by the arguments in Fodor et al. Fodor et al. misrepresent the form, function and scope of the decompositional hypothesis, and the procedures they employ to test for the psychological reality of definitions are flawed. I argue, further, that decompositional explanations of the phenomena they consider are preferable to their primitivist alternatives, and, hence, that there is prima facie reason to accept them as evidence for the existence of decompositional structure. Cognitive scientists would, therefore, do well to revert to their former commitment to the decompositional hypothesis. (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)

Over the past few decades, cognitive science has identified several forms of reasoning that make essential use of conceptual knowledge. Despite significant theoretical and empirical progress, there is still no unified framework for understanding how concepts are used in reasoning. This paper argues that the theory of conceptual spaces is capable of filling this gap. Our strategy is to demonstrate how various inference mechanisms which clearly rely on conceptual information—including similarity, typicality, and diagnosticity-based reasoning—can be (...) modeled using principles derived from conceptual spaces. Our first topic analyzes the role of expectations in inductive reasoning and their relation to the structure of our concepts. We examine the relationship between using generic expressions in natural language and common-sense reasoning as a second topic. We propose that the strength of a generic can be described by distances between properties and prototypes in conceptual spaces. Our third topic is category-based induction. We demonstrate that the theory of conceptual spaces can serve as a comprehensive model for this type of reasoning. The final topic is analogy. We review some proposals in this area, present a taxonomy of analogical relations, and show how to model them in terms of distances in conceptual spaces. We also briefly discuss the implications of the model for reasoning with concepts in artificial systems. (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)

Cognitive scientists have revealed systematic errors in human reasoning. There is disagreement about what these errors indicate about human rationality, but one upshot seems clear: human reasoning does not seem to fit traditional views of human rationality. This concern about rationality has made its way through various fields and has recently caught the attention of philosophers. The concern is that if philosophers are prone to systematic errors in reasoning, then the integrity of philosophy would be threatened. (...) In this paper, I present some of the more famous work in cognitive science that has marshaled this concern. Then I present reasons to think that those with training in philosophy will be less prone to certain systematic errors in reasoning. The suggestion is that if philosophers could be shown to be less prone to such errors, then the worries about the integrity of philosophy could be constrained. Then I present evidence that, according to performance on the CRT (Frederick 2005), those who have benefited from training and selection in philosophy are indeed less prone to one kind of systematic error: irrationally arbitrating between intuitive and reflective responses. Nonetheless, philosophers are not entirely immune to this systematic error, and their proclivity for this error is statistically related to their responses to a variety of philosophical questions. So, while the evidence herein puts constraints on the worries about the integrity of philosophy, it by no means eliminates these worries. The conclusion, then, is that the present evidence offers prima facie reasons to ascribe a mitigated privilege to philosophers' ability to rationally arbitrate between intuitive and reflective responses. (shrink)

Moral anxiety is the unease that we experience in the face of a novel or difficult moral decision, an unease that helps us recognize the significance of the issue we face and engages epistemic behaviors aimed at helping us work through it (reflection, information gathering, etc.). But recent discussions in philosophy raise questions about the value of moral anxiety (do we really do better when we’re anxious?); and work in cognitive science challenges its psychological plausibility (is there really (...) such an emotion?). Drawing on Kant and Kantians, I develop a model of moral anxiety (or ‘conscience’ in Kant’s terminology) that highlights both its empirical credentials and its distinctive value. Kant, it turns out, was an early—and sophisticated—dual-process theorist. (shrink)

Cognitive Optimization in the Age of AI: Enhancing Human Potential -/- Introduction -/- Cognitive optimization is the process of enhancing mental functions such as memory, learning, decision-making, and problem-solving to achieve peak intellectual performance. It is a multidisciplinary approach that integrates neuroscience, psychology, nutrition, lifestyle adjustments, and, increasingly, artificial intelligence (AI). In an era where information is abundant and rapid decision-making is crucial, optimizing cognitive abilities is more Important than ever. -/- AI-driven technologies, video games, mobile apps, (...) and digital platforms like YouTube are playing a transformative role in enhancing human cognition. YouTube, in particular, has become a powerful tool for self-directed learning, offering access to educational content, expert insights, and cognitive training exercises. -/- This essay explores cognitive optimization, key strategies involved, and how AI, video games, mobile apps, and platforms like YouTube are revolutionizing human intelligence. -/- The Science Behind Cognitive Optimization -/- Cognitive optimization is rooted in neuroplasticity—the brain’s ability to rewire itself through experience and learning. Several key factors contribute to cognitive enhancement: -/- 1. Neuroplasticity and Learning – Continuous learning strengthens neural connections, fostering intelligence and adaptability. Activities such as reading, solving complex problems, and learning new skills stimulate brain function. -/- 2. Nutrition and Brain Health – Diet plays a vital role in cognitive performance. Nutrients such as omega-3 fatty acids, antioxidants, and essential vitamins support brain function and protect against cognitive decline. -/- 3. Physical Exercise – Regular exercise increases blood flow to the brain, promotes neurogenesis (the growth of new neurons), and enhances memory and problem-solving skills. -/- 4. Sleep and Recovery – Sleep is essential for memory consolidation, emotional regulation, and mental clarity. Chronic sleep deprivation impairs cognitive function and decision-making. -/- 5. Mindfulness and Stress Management – Practices such as meditation, deep breathing, and yoga improve focus, reduce anxiety, and enhance mental resilience. -/- 6. Social Interaction and Collaboration – Engaging in meaningful discussions and debates strengthens cognitive agility and enhances problem-solving skills. -/- Beyond these traditional methods, digital tools such as AI-driven learning platforms, video games, mobile applications, and YouTube have expanded the possibilities for cognitive enhancement. -/- AI and Cognitive Optimization: A New Frontier -/- AI technology is revolutionizing cognitive optimization by providing personalized insights, accelerating learning, and even augmenting human intelligence. Below are several ways AI is transforming cognitive enhancement: -/- 1. AI-Powered Personalized Learning -/- AI-driven educational platforms such as adaptive learning systems customize lessons based on an individual’s learning style and pace. These systems use machine learning to analyze cognitive strengths and weaknesses, adjusting content dynamically to optimize learning efficiency. Platforms like Coursera, Duolingo, and Khan Academy utilize AI algorithms to provide personalized recommendations, ensuring users focus on areas that need improvement. -/- 2. Brain-Computer Interfaces (BCIs) -/- Brain-Computer Interfaces (BCIs) are AI-powered systems that enable direct communication between the human brain and computers. Companies like Neuralink and OpenBCI are developing BCIs that could enhance memory, restore lost cognitive functions, and even allow direct mental interaction with AI systems. This technology has the potential to revolutionize learning and decision-making by integrating human cognition with artificial intelligence. -/- 3. AI-Powered Cognitive Assistants -/- AI-driven virtual assistants such as ChatGPT, Google Assistant, and IBM Watson enhance cognition by providing instant access to information, summarizing complex topics, and even suggesting optimal decision-making strategies. These tools help individuals process vast amounts of information efficiently, reducing cognitive overload and enhancing productivity. -/- 4. AI in Mental Health and Stress Management -/- Mental health is a critical component of cognitive optimization. AI-driven mental health apps like Woebot and Wysa use machine learning to provide real-time emotional support, track mood patterns, and offer cognitive behavioral therapy (CBT) techniques. By reducing stress and anxiety, these AI-powered tools help maintain optimal cognitive function. -/- The Role of YouTube in Cognitive Optimization -/- YouTube has emerged as one of the most powerful platforms for cognitive enhancement. With millions of educational videos covering diverse subjects, YouTube serves as a free and accessible learning tool that fosters continuous cognitive growth. -/- 1. Learning New Skills and Expanding Knowledge -/- YouTube provides access to high-quality educational content in virtually every field. Channels like Veritasium, TED-Ed, and CrashCourse offer lessons on science, history, philosophy, and more. Learning new concepts regularly strengthens cognitive flexibility and enhances problem-solving skills. -/- 2. Enhancing Memory and Comprehension -/- Visual and auditory learning through YouTube helps reinforce memory retention. Watching documentaries, explainer videos, and step-by-step tutorials aids in deepening understanding and reinforcing neural pathways associated with knowledge acquisition. -/- 3. Improving Focus and Critical Thinking -/- Channels that discuss philosophy, logic, and critical thinking—such as Academy of Ideas or PBS Idea Channel—train the brain to analyze complex arguments, recognize biases, and develop sharper reasoning skills. Engaging in thought-provoking discussions through video content strengthens cognitive agility. -/- 4. AI-Generated Content for Personalized Learning -/- AI-powered recommendation algorithms help users discover personalized content based on their interests and learning habits. AI-curated video playlists allow individuals to engage in structured learning journeys, optimizing cognitive development in areas of personal interest. -/- 5. Interactive Learning and Problem-Solving -/- YouTube’s interactive features, such as quizzes, live Q&A sessions, and discussion threads, allow users to actively engage with educational content. This social interaction enhances cognitive engagement and retention. -/- By leveraging YouTube strategically, individuals can create personalized learning experiences that optimize cognitive function in a self-directed manner. -/- Video Games and Cognitive Optimization -/- Video games are increasingly recognized as tools for cognitive enhancement, providing interactive and engaging ways to improve various mental skills. -/- 1. Action Video Games for Reflexes and Decision-Making -/- Fast-paced action games like Call of Duty, Fortnite, and Counter-Strike train players to react quickly, improve hand-eye coordination, and develop strategic thinking under pressure. Studies suggest that such games enhance cognitive flexibility and decision-making speed. -/- 2. Puzzle and Strategy Games for Problem-Solving -/- Games like Portal, The Witness, and Tetris challenge players with complex puzzles that require logical thinking, spatial reasoning, and pattern recognition. -/- 3. Open-World and Role-Playing Games (RPGs) for Memory and Creativity -/- Games like The Legend of Zelda, Elden Ring, and The Witcher 3 encourage exploration, problem-solving, and strategic planning. -/- 4. Multiplayer and Cooperative Games for Social Cognition -/- Team-based games like League of Legends, Dota 2, and Among Us enhance communication skills, teamwork, and emotional intelligence. -/- The Future of Cognitive Optimization -/- The future of cognitive optimization lies in the seamless integration of AI, video games, mobile applications, and digital platforms like YouTube. Emerging technologies such as neuroprosthetics, AI-enhanced memory implants, and real-time brain augmentation could redefine human potential. -/- Furthermore, as AGI (Artificial General Intelligence) develops, AI could become an even more powerful tool in cognitive enhancement, potentially working alongside humans as cognitive partners. This could align with initiatives such as Angelito Malicse’s universal formula for decision-making, where AI-driven cognitive optimization ensures that human choices align with the natural law of balance. -/- Conclusion -/- Cognitive optimization is essential for maximizing human potential, and AI, video games, YouTube, and cognitive training apps are playing an increasingly significant role in this process. From personalized learning to interactive gaming and mobile applications, digital tools are transforming the way we enhance cognition. -/- By leveraging these tools responsibly and integrating them with fundamental cognitive enhancement strategies, humanity can unlock new levels of intelligence, creativity, and problem-solving ability—ensuring that the future of cognition is both powerful and sustainable. -/- . (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 article takes off from Johan van Benthem’s ruminations on the interface between logic and cognitive science in his position paper “Logic and reasoning: Do the facts matter?”. When trying to answer Van Benthem’s question whether logic can be fruitfully combined with psychological experiments, this article focuses on a specific domain of reasoning, namely higher-order social cognition, including attributions such as “Bob knows that Alice knows that he wrote a novel under pseudonym”. For intelligent interaction, it (...) is important that the participants recursively model the mental states of other agents. Otherwise, an international negotiation may fail, even when it has potential for a win-win solution, and in a time-critical rescue mission, a software agent may depend on a teammate’s action that never materializes. First a survey is presented of past and current research on higher-order social cognition, from the various viewpoints of logic, artificial intelligence, and psychology. Do people actually reason about each other’s knowledge in the way proscribed by epistemic logic? And if not, how can logic and cognitive science productively work together to construct more realistic models of human reasoning about other minds? The paper ends with a delineation of possible avenues for future research, aiming to provide a better understanding of higher-order social reasoning. The methodology is based on a combination of experimental research, logic, computational cognitive models, and agent-based evolutionary models. (shrink)

The published works of scientists often conceal the cognitive processes that led to their results. Scholars of mathematical practice must therefore seek out less obvious sources. This article analyzes a widely circulated mathematical joke, comprising a list of spurious proof types. An account is proposed in terms of argumentation schemes: stereotypical patterns of reasoning, which may be accompanied by critical questions itemizing possible lines of defeat. It is argued that humor is associated with risky forms of inference, which (...) are essential to creative mathematics. The components of the joke are explicated by argumentation schemes devised for application to topic-neutral reasoning. These in turn are classified under seven headings: retroduction, citation, intuition, meta-argument, closure, generalization, and definition. Finally, the wider significance of this account for the cognitive science of mathematics is discussed. (shrink)

Advancement in cognitive science depends, in part, on doing some occasional ‘theoretical housekeeping’. We highlight some conceptual confusions lurking in an important attempt at explaining the human capacity for rational or coherent thought: Thagard & Verbeurgt’s computational-level model of humans’ capacity for making reasonable and truth-conducive abductive inferences (1998; Thagard, 2000). Thagard & Verbeurgt’s model assumes that humans make such inferences by computing a coherence function (f_coh), which takes as input representation networks and their pair-wise constraints and gives (...) as output a partition into accepted (A) and rejected (R) elements that maximizes the weight of satisfied constraints. We argue that their proposal gives rise to at least three difficult problems. (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)

Cognitive scientists used to deem reasoning either as a higher cognitive process based on the manipulation of abstract rules or as a higher cognitive process that is stochastic rather than involving abstract rules. I maintain that these different perspectives are closely intertwined with a theoretical and methodological endorsement of either cognitivism or connectionism. Cognitivism and connectionism represent two prevailing and opposed paradigms in cognitive science. I aim to extoll the virtues of connectionist models of (...) enthymematic reasoning by following means: via the phenomenon of creative enthymeme, viz. the inference where one cannot even articulate the missing premise, I introduce a connectionist mechanism of pattern recognition as underlying expertise; via Gestalt switch or Gestalt click, I demonstrate how differences in pattern recognition of an expert and a novice can be construed as qualitatively different, and not merely a matter of faster reasoning. (shrink)