By applying research in artificial intelligence to problems in the philosophy of science, Paul Thagard develops an exciting new approach to the study of scientific reasoning. This approach uses computational ideas to shed light on how scientific theories are discovered, evaluated, and used in explanations. Thagard describes a detailed computational model of problem solving and discovery that provides a conceptually rich yet rigorous alternative to accounts of scientific knowledge based on formal logic, and he uses it to (...) illuminate such topics as the nature of concepts, hypothesis formation, analogy, and theory justification. (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..

In this path-breaking work, Paul Thagard draws on history and philosophy of science, cognitive psychology, and the field of artificial intelligence to develop a ...

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)

What is the relation between coherence and truth? This paper rejects numerous answers to this question, including the following: truth is coherence; coherence is irrelevant to truth; coherence always leads to truth; coherence leads to probability, which leads to truth. I will argue that coherence of the right kind leads to at least approximate truth. The right kind is explanatory coherence, where explanation consists in describing mechanisms. We can judge that a scientific theory is progressively approximating the truth if it (...) is increasing its explanatory coherence in two key respects: broadening by explaining more phenomena and deepening by investigating layers of mechanisms. I sketch an explanation of why deepening is a good epistemic strategy and discuss the prospect of deepening knowledge in the social sciences and everyday life. (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.

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 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)

This paper argues that questions concerning the nature of concepts that are central in cognitive psychology are also important to epistemology and that there is more to conceptual change than mere belief revision. Understanding of epistemic change requires appreciation of the complex ways in which concepts are structured and organized and of how this organization can affect belief revision. Following a brief summary of the psychological functions of concepts and a discussion of some recent accounts of what concepts are, I (...) propose a view of concepts as complex computational structures. This account suggests that conceptual change can come in varying degrees, with the most extreme consisting of fundamental conceptual reorganizations. These degrees of conceptual change are illustrated by the development of the concept of an acid. (shrink)

Conceptual combinations range from the utterly mundane to the sublimely creative. Mundane combinations include a myriad of adjective-noun and noun-noun juxtapositions that crop up in everyday speaking and writing, such as blue car, cooked carrots, and radio phone. Creative combinations include some of the most important theoretical constructions in science, such as sound wave, bacterial infection, and natural selection. Both mundane and creative conceptual combinations are essential to our attempts to make sense of the world and people's utterances about it. (...) This paper will show how the various aspects of conceptual combination discussed by Hampton (this volume), Shoben and Gagn. (shrink)

"This is a wonderful book! In "How Scientists Explain Disease," Paul Thagard offers us a delightful essay combining science, its history, philosophy, and sociology.

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)

The book integrates decades of multidisciplinary research, but its clear explanations and humor make it accessible to the general reader.

Science is studied in very different ways by historians, philosophers, psychologists, and sociologists. Not only do researchers from different fields apply markedly different methods, they also tend to focus on apparently disparate aspects of science. At the farthest extremes, we find on one side some philosophers attempting logical analyses of scientific knowledge, and on the other some sociologists maintaining that all knowledge is socially constructed. This paper is an attempt to view history, philosophy, psychology, and sociology of science from a (...) unified perspective. (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)

This paper presents a theory and computational model of the role of emotions in group decision making. After reviewing the role of emotions in individual decision making, it describes social and psychological mechanisms by which emotional and other information is transmitted between individuals. The processes by which these mechanisms can contribute to group consensus are modeled computationally using a program, HOTCO 3, which has been used to simulate simple cases of emotion-based group decision making.

This paper evaluates four competing psychological explanations for why the jury in the O.J. Simpson murder trial reached the verdict they did: explanatory coherence, Bayesian probability theory, wishful thinking, and emotional coherence. It describes computational models that provide detailed simulations of juror reasoning for explanatory coherence, Bayesian networks, and emotional coherence, and argues that the latter account provides the most plausible explanation of the jury's decision.

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)

Despite the growing appreciation of the relevance of affect to cognition, analogy researchers have paid remarkably little attention to emotion. This paper discusses three general classes of analogy that involve emotions. The most straightforward are analogies and metaphors about emotions, for example "Love is a rose and you better not pick it." Much more interesting are analogies that involve the transfer of emotions, for example in empathy in which people understand the emotions of others by imagining their own emotional reactions (...) in similar situations. Finally, there are analogies that generate emotions, for example analogical jokes that generate emotions such as surprise and amusement. (shrink)

This paper naturalizes inductive inference by showing how scientific knowledge of real mechanisms provides large benefits to it. I show how knowledge about mechanisms contributes to generalization, inference to the best explanation, causal inference, and reasoning with probabilities. Generalization from some A are B to all A are B is more plausible when a mechanism connects A to B. Inference to the best explanation is strengthened when the explanations are mechanistic and when explanatory hypotheses are themselves mechanistically explained. Causal inference (...) in medical explanation, counterfactual reasoning, and analogy also benefit from mechanistic connections. Mechanisms also help with problems concerning the interpretation, availability, and computation of probabilities. (shrink)

Almost all computational models of the mind and brain ignore details about neurotransmitters, hormones, and other molecules. The neglect of neurochemistry in cognitive science would be appropriate if the computational properties of brains relevant to explaining mental functioning were in fact electrical rather than chemical. But there is considerable evidence that chemical complexity really does matter to brain computation, including the role of proteins in intracellular computation, the operations of synapses and neurotransmitters, and the effects of neuromodulators such as hormones. (...) Neurochemical computation has implications for understanding emotions, cognition, and artificial intelligence. (shrink)

Machine learning is the study of algorithms that enable computers to improve their performance and increase their knowledge base. Research in machine learning has taken place since the beginning of artificial intelligence in the mid‐1950s. The first notable success was Arthur Samuel's program that learned to play checkers well enough to beat skilled humans. The program estimated the best move in a situation by using a mathematical function whose sixteen parameters describe board positions, and it improved its performance by adjusting (...) weights on the parameters in order to generalize about what moves were successful. (shrink)

This paper is a critique of Darwinian models of the growth of scientific knowledge. Donald Campbell, Karl Popper, Stephen Toulmin, and others have discussed analogies between the development of biological species and the development of scientific knowledge: in both kinds of development, we find variation, selection, and transmission. It is argued that these similarities are superficial, and that closer examination of biological evolution and of the history of science shows that a non-Darwinian approach to historical epistemology is needed. An adequate (...) model of the growth of knowledge will have to go beyond evolutionary epistemology in discussing the role of intentional, abductive theory construction in scientific discovery, the selection of theories according to general criteria, the achievement of progress by sustained application of criteria, and the transmission of selected theories in highly organized scientific communities. (shrink)

Computer models provide formal techniques that are highly relevant to philosophical issues in epistemology, metaphysics, and ethics. Such models can help philosophers to address both descriptive issues about how people do think and normative issues about how people can think better. The use of computer models in ways similar to their scientific applications substantially extends philosophical methodology beyond the techniques of thought experiments and abstract reflection. For formal philosophy, computer models offer a much broader range of representational techniques than are (...) found in traditional logic, probability, and set theory, taking into account the important roles of imagery, analogy, and emotion in human thinking. Computer models make possible investigation of the dynamics of inference, not just abstract formal relations. (shrink)

Explanations of the growth of scientific knowledge can be characterized in terms of logical, cognitive, and social schemas. But cognitive and social schemas are complementary rather than competitive, and purely social explanations of scientific change are as inadequate as purely cognitive explanations. For example, cognitive explanations of the chemical revolution must be supplemented by and combined with social explanations, and social explanations of the rise of the mechanical world view must be supplemented by and combined with cognitive explanations. Rational appraisal (...) of cognitive and social strategies for improving knowledge should appreciate the interdependence of mind and society. (shrink)

Computational models can aid in the development of philosophical views concerning the structure and growth of scientific knowledge. In cognitive psychology, computational models have proved valuable for describing the structures and processes of thought and for testing these models by writing and running computer programs using the techniques of artificial intelligence. Similarly, in the philosophy of science models can be developed that shed light on the structure, discovery, and justification of scientific theories. This paper briefly describes a computational model of (...) problem solving and learning that has been used to simulate several kinds of scientific reasoning. (shrink)

This paper provides a computational characterization of coherence that applies to a wide range of philosophical problems and psychological phenomena. Maximizing coherence is a matter of maximizing satisfaction of a set of positive and negative constraints. After comparing five algorithms for maximizing coherence, we show how our characterization of coherence overcomes traditional philosophical objections about circularity and truth.

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)

Substrate independence and mind-body functionalism claim that thinking does not depend on any particular kind of physical implementation. But real-world information processing depends on energy, and energy depends on material substrates. Biological evidence for these claims comes from ecology and neuroscience, while computational evidence comes from neuromorphic computing and deep learning. Attention to energy requirements undermines the use of substrate independence to support claims about the feasibility of artificial intelligence, the moral standing of robots, the possibility that we may be (...) living in a computer simulation, the plausibility of transferring minds into computers, and the autonomy of psychology from neuroscience. (shrink)

In 1983, Dr. J. Robin Warren and Dr. Barry Marshall reported finding a new kind of bacteria in the stomachs of people with gastritis. Warren and Marshall were soon led to the hypothesis that peptic ulcers are generally caused, not by excess acidity or stress, but by a bacterial infection. Initially, this hypothesis was viewed as preposterous, and it is still somewhat controversial. In 1994, however, a U. S. National Institutes of Health Consensus Development Panel concluded that infection appears to (...) play an important contributory role in the pathogenesis of peptic ulcers, and recommended that antibiotics be used in their treatment. Peptic ulcers are common, affecting up to 10% of the population, and evidence has mounted that many ulcers can be cured by eradicating the bacteria responsible for them. (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)

This article challenges the common view that improvements in critical thinking are best pursued by investigations in informal logic. From the perspective of research in psychology and neuroscience, hu-man inference is a process that is multimodal, parallel, and often emo-tional, which makes it unlike the linguistic, serial, and narrowly cog-nitive structure of arguments. At-tempts to improve inferential prac-tice need to consider psychological error tendencies, which are patterns of thinking that are natural for peo-ple but frequently lead to mistakes in judgment. (...) This article discusses two important but neglected error ten-dencies: motivated inference and fear-driven inference. (shrink)

Although mind-brain identity remains controversial, many other identities of ordinary things with scientific ones are well established. For example, air is a mixture of gases, water is H2O, and fire is rapid oxidation. This paper examines the history of 15 important identifications: air, blood, cloud, earth, electricity, fire, gold, heat, light, lightning, magnetism, salt, star, thunder, and water. This examination yields surprising conclusions about the nature of justification, explanation, and conceptual change.

abstract This paper is an investigation of the moral psychology of decisions that involve a conflict of interest. It draws on the burgeoning field of affective neuroscience, which is the study of the neurobiology of emotional systems in the brain. I show that a recent neurocomputational model of how the brain integrates cognitive and affective information in decision‐making can help to answer some important descriptive and normative questions about the moral psychology of conflicts of interest. These questions include: Why are (...) decisions that involve conflicts of interest so common? Why are people so often unaware that they are acting immorally as the result of conflicts of interest? What is the relation of conflicts of interest to other kinds of irrationality, especially self‐deception and weakness of will? What psychological, social, and logical steps can be taken to reduce the occurrence of immoral decisions resulting from conflicts of interest? I discuss five strategies for dealing with conflicts of interest: avoidance, optimal reasoning patterns, disclosure, social oversight, and understanding of neuropsychological processes. (shrink)

By contrasting Hippocratic and nineteenth century theories of disease, this paper describes important conceptual changes that have taken place in the history of medicine. Disease concepts are presented as causal networks that represent the relations among the symptoms, causes, and treatment of a disease. The transition to the germ theory of disease produced dramatic conceptual changes as the result of a radically new view of disease causation. An analogy between disease and fermentation was important for two of the main developers (...) of the germ theory of disease, Pasteur and Lister. Attention to the development of germ concepts shows the need for a referential account of conceptual change to complement a representational account. (shrink)

Keith Holyoak and Paul Thagard provide a unified, comprehensive account of the diverse operations and applications of analogy, including problem solving, ...

My description of the cognitive processes involved in the discovery, development, and acceptance of the bacterial theory of ulcers might have left the impression that science is all in the mind (Thagard, forthcoming-b). But only part of the story of the bacterial theory of ulcers is psychological. This paper discusses the important role of physical interaction with the world by means of instruments and experiments, and the equally important role of social interactions among the medical researchers who developed the (...) theory. The main questions I want to answer are the following: 1. What instruments contributed to the development and acceptance of the new theory? 2. What kinds of experiments contributed to the development and acceptance of the new theory? 3. How did theorizing and experimentation interact in the development of new experiments and hypotheses? 4. How did social processes such as collaboration, communication, and consensus contribute to the development and widespread acceptance of the bacterial theory of ulcers? I conclude with a sketch of science as a complex system of interacting psychological, physical, and social processes. (shrink)

Paul Thagard describes how his current work in neurophilosophy grew out of a long series of engagements with philosophy, philosophy of science, cognitive science, neural networks, and theoretical neuroscience. Each of these engagements had cumulative advantages over its predecessors. Neurophilosophy is prospering by applying insights about the workings of the brain to central problems in epistemology, metaphysics, and ethics.