This target article presents a new computational theory of explanatory coherence that applies to the acceptance and rejection of scientific hypotheses as well as to reasoning in everyday life, The theory consists of seven principles that establish relations of local coherence between a hypothesis and other propositions. A hypothesis coheres with propositions that it explains, or that explain it, or that participate with it in explaining other propositions, or that offer analogous explanations. Propositions are incoherent with each other if they (...) are contradictory, Propositions that describe the results of observation have a degree of acceptability on their own. An explanatory hypothesis is acccpted if it coheres better overall than its competitors. The power of the seven principles is shown by their implementation in a connectionist program called ECHO, which treats hypothesis evaluation as a constraint satisfaction problem. Inputs about the explanatory relations are used to create a network of units representing propositions, while coherende and incoherence relations are encoded by excitatory and inbihitory links. ECHO provides an algorithm for smoothly integrating theory evaluation based on considerations of explanatory breadth, simplicity, and analogy. It has been applied to such important scientific cases as Lovoisier's argument for oxygen against the phlogiston theory and Darwin's argument for evolution against creationism, and also to cases of legal reasoning. The theory of explanatory coherence has implications for artificial intelligence, psychology, and philosophy. (shrink)
Contrary to standard assumptions, reasoning is often an emotional process. Emotions can have good effects, as when a scientist gets excited about a line of research and pursues it successfully despite criticism. But emotions can also distort reasoning, as when a juror ignores evidence of guilt just because the accused seems like a nice guy. In _Hot Thought_, Paul Thagard describes the mental mechanisms -- cognitive, neural, molecular, and social -- that interact to produce different kinds of human thinking, from (...) everyday decision making to legal reasoning, scientific discovery, and religious belief, and he discusses when and how thinking and reasoning should be emotional. Thagard argues that an understanding of emotional thinking needs to integrate the cognitive, neural, molecular, and social levels. Many of the chapters employ computational models of various levels of thinking, including HOTCO models and the more neurologically realistic GAGE model. Thagard uses these models to illuminate thinking in the domains of law, science, and religion, discussing such topics as the role of doubt and reasonable doubt in legal and other contexts, valuable emotional habits for successful scientists, and the emotional content of religious beliefs. Identifying and assessing the impact of emotion, Thagard argues, can suggest ways to improve the process of reasoning. (shrink)
A description of mental mechanisms that explain how emotions influence thought, from everyday decision making to scientific discovery and religious belief, and an analysis of when emotion can contribute to good reasoning.
Using astrology as a case study, this paper attempts to establish a criterion for demarcating science from pseudoscience. Numerous reasons for considering astrology to be a pseudoscience are evaluated and rejected; verifiability and falsifiability are briefly discussed. A theory is said to be pseudoscientific if and only if (1) it has been less progressive than alternative theories over a long period of time, and faces many unsolved problems, but (2) the community of practitioners makes little attempt to develop the theory (...) towards solutions of the problems, shows no concern for attempts to evaluate the theory in relation to others, and is selective in considering confirmations and disconfirmations. This criterion has the interesting consequence that a theory can be scientific at one time but pseudoscientific at another. (shrink)
Many kinds of creativity result from combination of mental representations. This paper provides a computational account of how creative thinking can arise from combining neural patterns into ones that are potentially novel and useful. We defend the hypothesis that such combinations arise from mechanisms that bind together neural activity by a process of convolution, a mathematical operation that interweaves structures. We describe computer simulations that show the feasibility of using convolution to produce emergent patterns of neural activity that can support (...) cognitive and emotional processes underlying human creativity. (shrink)
A biochemical pathway is a sequence of chemical reactions in a biological organism. Such pathways specify mechanisms that explain how cells carry out their major functions by means of molecules and reactions that produce regular changes. Many diseases can be explained by defects in pathways, and new treatments often involve finding drugs that correct those defects. This paper presents explanation schemas and treatment strategies that characterize how thinking about pathways contributes to biomedical discovery. It discusses the significance of pathways for (...) understanding the nature of diseases, explanations, and theories. (shrink)
The reconciliation of theories of concepts based on prototypes, exemplars, and theory-like structures is a longstanding problem in cognitive science. In response to this problem, researchers have recently tended to adopt either hybrid theories that combine various kinds of representational structure, or eliminative theories that replace concepts with a more finely grained taxonomy of mental representations. In this paper, we describe an alternative approach involving a single class of mental representations called “semantic pointers.” Semantic pointers are symbol-like representations that result (...) from the compression and recursive binding of perceptual, lexical, and motor representations, effectively integrating traditional connectionist and symbolic approaches. We present a computational model using semantic pointers that replicates experimental data from categorization studies involving each prior paradigm. We argue that a framework involving semantic pointers can provide a unified account of conceptual phenomena, and we compare our framework to existing alternatives in accounting for the scope, content, recursive combination, and neural implementation of concepts. (shrink)
This paper proposes a theory of how conscious emotional experience is produced by the brain as the result of many interacting brain areas coordinated in working memory. These brain areas integrate perceptions of bodily states of an organism with cognitive appraisals of its current situation. Emotions are neural processes that represent the overall cognitive and somatic state of the organism. Conscious experience arises when neural representations achieve high activation as part of working memory. This theory explains numerous phenomena concerning emotional (...) consciousness, including diﬀerentiation, integration, intensity, valence, and change. Ó 2007 Elsevier Inc. All rights reserved. (shrink)
We propose a unified theory of intentions as neural processes that integrate representations of states of affairs, actions, and emotional evaluation. We show how this theory provides answers to philosophical questions about the concept of intention, psychological questions about human behavior, computational questions about the relations between belief and action, and neuroscientific questions about how the brain produces actions. Our theory of intention ties together biologically plausible mechanisms for belief, planning, and motor control. The computational feasibility of these mechanisms is (...) shown by a model that simulates psychologically important cases of intention. (shrink)
Contrary to common views that philosophy is extraneous to cognitive science, this paper argues that philosophy has a crucial role to play in cognitive science with respect to generality and normativity. General questions include the nature of theories and explanations, the role of computer simulation in cognitive theorizing, and the relations among the different ﬁelds of cognitive science. Normative questions include whether human thinking should be Bayesian, whether decision making should maximize expected utility, and how norms should be established. These (...) kinds of general and normative questions make philosophical reﬂection an important part of progress in cognitive science. Philosophy operates best, however, not with a priori reasoning or conceptual analysis, but rather with empirically informed reﬂection on a wide range of ﬁndings in cognitive science. (shrink)
Cognitive science is the interdisciplinary investigation of mind and intelligence, embracing psychology, neuroscience, anthropology, artificial intelligence, and philosophy. There are many important philosophical questions related to this investigation, but this short chapter will focus on the following three. What is the nature of the explanations and theories developed in cognitive science? What are the relations among the five disciplines that comprise cognitive science? What are the implications of cognitive science research for general issues in the philosophy of science? I will (...) argue that cognitive theories and explanations depend on representations of mechanisms and that the relations among the five disciplines, especially psychology and neuroscience, depend on relations between kinds of mechanisms. These conclusions have implications for central problems in general philosophy of science such as the nature of theories, explanations, and reduction between theories at different levels. (shrink)
This paper investigates the revolutionary conceptual changes that took place when the phlogiston theory of Stahl was replaced by the oxygen theory of Lavoisier. Using techniques drawn from artificial intelligence, it represents the crucial stages in Lavoisier's conceptual development from 1772 to 1789. It then sketches a computational theory of conceptual change to account for Lavoisier's discovery of the oxygen theory and for the replacement of the phlogiston theory.
Collaboration is ubiquitous in the natural and social sciences. How collaboration contributes to the development of scientific knowledge can be assessed by considering four different kinds of collaboration in the light of Alvin Goldman's five standards for appraising epistemic practices. A sixth standard is proposed to help understand the importance of theoretical collaborations in cognitive science and other fields. I illustrate the application of these six standards by describing two recent scientific developments in which collaboration has been important, the bacterial (...) theory of ulcers and the multiconstraint theory of analogy, and by arguing that philosophy should become more collaborative. (shrink)
Paul Thagard uses new accounts of brain mechanisms and social interactions to forge theories of mind, knowledge, reality, morality, justice, meaning, and the arts. Natural Philosophy brings new methods for analyzing concepts, understanding values, and achieving coherence. It shows how to unify the humanities with the cognitive and social sciences.
Quine and others have recommended principles of charity which discourage judgments of irrationality. Such principles have been proposed to govern translation, psychology, and economics. After comparing principles of charity of different degrees of severity, we argue that the stronger principles are likely to block understanding of human behavior and impede progress toward improving it. We support a moderate principle of charity which leaves room for empirically justified judgments of irrationality.
A philosopher once asked me: “Paul, how do you collaborate?” He was puzzled about how I came to have more than two dozen co-authors over the past 20 years. His puzzlement was natural for a philosopher, because co-authored articles and books are still rare in philosophy and the humanities, in contrast to science where most current research is collaborative. Unlike most philosophers, scientists know how to collaborate; this paper is about the nature of such procedural knowledge. I begin by discussing (...) three related distinctions found in philosophy and cognitive science: knowledge how vs. knowledge that, procedural vs. declarative knowledge, and explicit vs. implicit knowledge. I then document the prevalence of collaboration in the sciences and its scarcity in philosophy. In order to characterize the sorts of procedural knowledge that make collaborative research possible and fruitful, I discuss how scientists collaborate, how they learn to collaborate, and why they collaborate. Contrary to some recent suggestions by philosophers, I will argue that knowledge how often does not always reduce to knowledge that, and that collaboration has many purposes besides the pursuit of power and resources. The relative scarcity of philosophical collaborations might be explained by the nature of philosophy, if the field is viewed as inherently personal or a priori. But I argue against this view in favor of a more naturalistic one, December 2, 2005 with the implication that the main reason why philosophers do not collaborate more is that they do not know how. My account of collaboration is based on my own experience, published advice by practicing scientists, and interviews with a group of highly successful scientific collaborators who are members of the Social Psychology area of the University of Waterloo Psychology Department. For the past two decades, Waterloo’s social psychology program has flourished, both in collaborative publication and in graduate training: their former Ph.D.. (shrink)
This paper develops a descriptive and normative account of how people respond to testimony. It postulates a default pathway in which people more or less automatically respond to a claim by accepting it, as long as the claim made is consistent with their beliefs and the source is credible. Otherwise, people enter a reflective pathway in which they evaluate the claim based on its explanatory coherence with everything else they believe. Computer simulations show how explanatory coherence can be maximized in (...) real-life cases, taking into account all the relevant evidence including the credibility of whoever is making a claim. The explanatory-coherence account is more plausible both descriptively and normatively than a Bayesian account. (shrink)
states are to be understood in terms of their functional relationships to other mental states, not in terms of their material instantiation in any particular kind of hardware. But the argument that material instantiation is irrelevant to functional..
We examine the use of analogy in human thinking from the perspective of a multiconstraint theory, which postulates three basic types of constraints: similarity, structure and purpose. The operation of these constraints is apparent in both laboratory experiments on analogy and in naturalistic settings, including politics, psychotherapy, and scientific research. We sketch how the multiconstraint theory can be implemented in detailed computational simulations of the analogical human mind.
We argue that computation via quantum mechanical processes is irrelevant to explaining how brains produce thought, contrary to the ongoing speculations of many theorists. First, quantum effects do not have the temporal properties required for neural information processing. Second, there are substantial physical obstacles to any organic instantiation of quantum computation. Third, there is no psychological evidence that such mental phenomena as consciousness and mathematical thinking require explanation via quantum theory. We conclude that understanding brain function is unlikely to require (...) quantum computation or similar mechanisms. (shrink)
Thought experiments have been influential in philosophy at least since Plato, and they have contributed to science at least since Galileo. Some of this influence is appropriate, because thought experiments can have legitimate roles in generating and clarifying hypotheses, as well as in identifying problems in competing hypotheses. I will argue, however, that philosophers have often overestimated the significance of thought experiments by supposing that they can provide evidence that supports the acceptance of beliefs. Accepting hypotheses merely on the basis (...) of thinking about them constitutes a kind of epistemic hubris with many negative consequences, including the acquisition of false beliefs and the blocking of .. (shrink)
Why do people get sick? I argue that a disease explanation is best thought of as causal network instantiation, where a causal network describes the interrelations among multiple factors, and instantiation consists of observational or hypothetical assignment of factors to the patient whose disease is being explained. This paper first discusses inference from correlation to causation, integrating recent psychological discussions of causal reasoning with epidemiological approaches to understanding disease causation, particularly concerning ulcers and lung cancer. It then shows how causal (...) mechanisms represented by causal networks can contribute to reasoning involving correlation and causation. The understanding of causation and causal mechanisms provides the basis for a presentation of the causal network instantiation model of medical explanation. (shrink)
Bradford Hill (1965) highlighted nine aspects of the complex evidential situation a medical researcher faces when determining whether a causal relation exists between a disease and various conditions associated with it. These aspects are widely cited in the literature on epidemiological inference as justifying an inference to a causal claim, but the epistemological basis of the Hill aspects is not understood. We offer an explanatory coherentist interpretation, explicated by Thagard's ECHO model of explanatory coherence. The ECHO model captures the complexity (...) of epidemiological inference and provides a tractable model for inferring disease causation. We apply this model to three cases: the inference of a causal connection between the Zika virus and birth defects, the classic inference that smoking causes cancer, and John Snow’s inference about the cause of cholera. (shrink)
The aim of this paper is to describe a methodology for revising logical principles in the light of empirical psychological findings. Historical philosophy of science and wide reflective equilibrium in ethics are considered as providing possible models for arguing from the descriptive to the normative. Neither is adequate for the psychology/logic case, and a new model is constructed, employing criteria for evaluating inferential systems. Once we have such criteria, the notion of reflective equilibrium becomes redundant.
Since Plato, most philosophers have drawn a sharp line between reason and emotion, assuming that emotions interfere with rationality and have nothing to contribute to good reasoning. In his dialogue the Phaedrus, Plato compared the rational part of the soul to a charioteer who must control his steeds, which correspond to the emotional parts of the soul (Plato 1961, p. 499). Today, scientists are often taken as the paragons of rationality, and scientific thought is generally assumed to be independent of (...) emotional thinking. (shrink)
The authors present a neurological theory of how cognitive information and emotional information are integrated in the nucleus accumbens during effective decision making. They describe how the nucleus accumbens acts as a gateway to integrate cognitive information from the ventromedial prefrontal cortex and the hippocampus with emotional information from the amygdala. The authors have modeled this integration by a network of spiking artificial neurons organized into separate areas and used this computational model to simulate 2 kinds of cognitive–affective integration. The (...) model simulates successful performance by people with normal cognitive–affective integration. The model also simulates the historical case of Phineas Gage as well as subsequent patients whose ability to make decisions became.. (shrink)
Students face many important decisions: What college or university should I attend? What should I study? What kind of job should I try to get? Which people should I hang out with? Should I continue or break off a relationship? Should I get married? Should I have a baby? What kind of medical treatment should I use? A theory of practical reasoning should have something to say about how students and other people can improve their decision making.
This paper proposes that self-deception results from the emotional coherence of beliefs with subjective goals. We apply the HOTCO computational model of emotional coherence to simulate a rich case of self-deception from Hawthorne's The Scarlet Letter.We argue that this model is more psychologically realistic than other available accounts of self-deception, and discuss related issues such as wishful thinking, intention, and the division of the self.
This paper examines Alvin Goldman's discussion of acceptance and uncertainty in chapter 15 of his book, Epistemology and Cognition. Goldman discusses how acceptance and rejection of beliefs might be understood in terms of "winner-take-all" connectionist networks. The paper answers some of the questions he raises in his epistemic evaluation of connectionist programs. The major tool for doing this is a connectionist model of explanatory coherence judgments (Thagard, Behavioral and Brain Sciences, 1989). Finally, there is a discussion of problems for Goldman's (...) general epistemological project that arise if one adopts a different approach to connectionism based on distributed representations. (shrink)
This paper uses the economic crisis of 2008 as a case study to examine the explanatory validity of collective mental representations. Distinguished economists such as Paul Krugman and Joseph Stiglitz attribute collective beliefs, desires, intentions, and emotions to organizations such as banks and governments. I argue that the most plausible interpretation of these attributions is that they are metaphorical pointers to a complex of multilevel social, psychological, and neural mechanisms. This interpretation also applies to collective knowledge in science: scientific communities (...) do not literally have collective representations, but social mechanisms do make important contributions to scientific knowledge. (shrink)