This paper discusses abductive reasoning---that is, reasoning in which explanatory hypotheses are formed and evaluated. First, it criticizes two recent formal logical models of abduction. An adequate formalization would have to take into account the following aspects of abduction: explanation is not deduction; hypotheses are layered; abduction is sometimes creative; hypotheses may be revolutionary; completeness is elusive; simplicity is complex; and abductive reasoning may be visual and non-sentential. Second, in order to illustrate visual aspects of hypothesis formation, the paper describes (...) recent work on visual inference in archaeology. Third, in connection with the evaluation of explanatory hypotheses, the paper describes recent results on the computation of coherence. (shrink)

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.

In their introduction to this volume, Ram and Leake usefully distinguish between task goals and learning goals. Task goals are desired results or states in an external world, while learning goals are desired mental states that a learner seeks to acquire as part of the accomplishment of task goals. We agree with the fundamental claim that learning is an active and strategic process that takes place in the context of tasks and goals (see also Holland, Holyoak, Nisbett, and Thagard, 1986). (...) But there are important questions about the nature of goals that have rarely been addressed. First, how can a cognitive system deal with incompatible task goals? Someone may want both to get lots of research done and to relax and have fun with his or her friends. Learning how to accomplish both these tasks will take place in the context of goals that cannot be fully realized together. Second, how are goals chosen in the first place and why are some goals judged to be more important than others? People do not simply come equipped with goals and priorities: we sometimes have to learn what is important to us by adjusting the importance of goals in the context of other compatible and incompatible goals. This paper presents a theory and a computational model of how goals can be adopted or rejected in the context of decision making. In contrast to classical decision theory, it views decision making as a process not only of choosing actions but also of evaluating goals. Our theory can therefore be construed as concerned with the goal-directed learning of goals. (shrink)

Computer modelling of personality and behaviour is becoming increasingly important in many fields of computer science and psychology. Personality and emotion-driven Believable Agents are needed in areas like human–machine interfaces, electronic advertising and, most notably, electronic entertainment. Computer models of personality can help explain personality by illustrating its underlying structure and dynamics. This work presents a neural network model of personality and personality change. The goals are to help understand personality and create more realistic and believable characters for interactive video (...) games. The model is based largely on trait theories of personality. Behaviour in the model results from the interaction of three components: personality-based predispositions for behaviour, moods/emotions and environmental situations. Personality develops gradually over time depending on the situations encountered. Modelling personality change produces interesting and believable virtual characters whose behaviours change in psychologically plausible ways. (shrink)

Computer science only became established as a field in the 1950s, growing out of theoretical and practical research begun in the previous two decades. The field has exhibited immense creativity, ranging from innovative hardware such as the early mainframes to software breakthroughs such as programming languages and the Internet. Martin Gardner worried that "it would be a sad day if human beings, adjusting to the Computer Revolution, became so intellectually lazy that they lost their power of creative thinking" (Gardner, 1978, (...) p. vi-viii). On the contrary, computers and the theory of computation have provided great opportunities for creative work. This chapter examines several key aspects of creativity in computer science, beginning with the question of how problems arise in computer science. We then discuss the use of analogies in solving key problems in the history of computer science. Our discussion in these sections is based on historical examples, but the following sections discuss the nature of creativity using information from a contemporary source, a set of interviews with practicing computer scientists collected by the Association of Computing Machinery’s on-line student magazine, Crossroads. We then provide a general comparison of creativity in computer science and in the natural sciences. (shrink)

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)

According to Church’s thesis, we can identify the intuitive concept of effective computability with such well-defined mathematical concepts as Turing computability and partial recursiveness. The almost universal acceptance of Church’s thesis among logicians and computer scientists is puzzling from some epistemological perspectives, since no formal proof is possible of a thesis that involves an informal concept such as effectiveness. Elliott Mendelson has recently argued, however, that equivalencies between intuitive notions and precise notions need not always be considered unprovable theses, and (...) that Church’s thesis should be accepted as true.I want to discuss a thesis that is nearly as important in current research in computer science as Church’s thesis. I call the newer thesis the tractability thesis, since it identifies the intuitive class of computationally tractable problems with a precise class of problems whose solutions can be computed in polynomial time. After briefly reviewing the theory of intractability, I compare the grounds for accepting the tractability thesis with the grounds for accepting Church's thesis. Intimately connected with the tractability thesis is the mathematical conjecture, whose meaning I shall shortly explain, that P≠NP. Unlike Church's thesis, this conjecture is precise enough to be capable of mathematical proof, but most computer scientists believe it even though no proof has been found. As we shall see below, understanding the grounds for acceptance of the conjecture that P≠NP has implications for general questions in the philosophy of mathematics and science, especially concerning the epistemological importance of explanatory and conceptual coherence. (shrink)

Este artigo investiga as mudanças conceituais revolucionárias que ocorreram quando a teoria do flogisto de Stahl foi substituída pela teoria do oxigênio de Lavoisier. Utilizando técnicas extraídas da inteligência artificial, o artigo descreve os estágios cruciais no desenvolvimento conceitual de Lavoisier, de 1772 até 1789. Em seguida, é esboçada uma teoria computacional da mudança conceitual de modo a explicar a descoberta de Lavoisier da teoria do oxigênio e a substituiçáo da teoria do flogisto. Este artigo é uma traduçáo de “The (...) Conceptual Structure of The Chemical Revolution”, publicado originalmente em Philosophy of Science , número 57, p. 183-209, 1990. Todos os direitos do artigo pertencem à revista Philosophy of Science , editada pela University of Chicago Press. O copyright do artigo original é de 1990, da Philosophy of Science Association. Os tradutores agradecem a Paul Thagard e a Philosophy of Science a permissáo para esta traduçáo. [NT.]. (shrink)

Barnes, A. and P. Thagard Empathy and analogy. Dialogue: Canadian Philosophical Review, 36: 705-720. HTML Croft, D., & Thagard, P.. Dynamic imagery: A computational model of motion and visual analogy. In L. Magnani and N. Nersessian, Model-based reasoning: Science, technology, values. New York: Kluwer/Plenum, 259-274. PDF only. HTML description of program and code for DIVA.

This is an excerpt from the contentMost academics have heard of deduction and induction, but much less familiar is the kind of inference that the American philosopher Charles Peirce called abduction. Abductive inference is the generation and evaluation of explanatory hypotheses, a kind of reasoning that is far more common and important than deductions, which rarely occur outside of mathematics, and inductions from examples to generalizations. Lorenzo Magnani has produced a magnum opus on abduction that brilliantly spans its philosophical, neuropsychological, (...) computational, and ecological dimensions. In this review I will briefly highlight some of the substantial contributions of Abductive Cognition and raise a few objections to it. I finish by briefly discussing the relevance of abduction to concerns about mind and society. Magnani’s treatise is by far the most comprehensive discussion of abductive thinking to date. In the first chapter, he reviews various ways of thinking about abduction, ranging from sentential approac. (shrink)

Jean-Frédéric de Pasquale ,Pierre Poirier.

Like Glenn Shafer, we are nostalgic for the time when “philosophers, mathematicians, and scientists interested in probability, induction, and scientific methodology talked with each other more than they do now”, [p.10]. 1 Shafer goes on to mention other relevant contemporary communities. He himself has been at the interface of many of these communities while at the same time making major contributions to them and this very symposium represents something of that desired discussion. We begin with a couple of general points (...) about issues several commentators have raised and then discuss other more particular issues. (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)

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)

This article examines some of the most important metaphors and analogies that epistemologists have used to discuss the structure and validity of knowledge. After reviewing foundational, coherentist, and other metaphors for knowledge, we discuss the metaphilosophical significance of the prevalence of such metaphors. We argue that they support a view of philosophy as akin to science rather than poetry or rhetoric.

This paper examines some of the most important metaphors and analogies that epistemologists have used to discuss the structure and validity of knowledge. After reviewing foundational, coherentist, and other metaphors for knowledge, we discuss the metaphilosophical significance of the prevalence of such metaphors. We argue that they support a view of philosophy as akin to science rather than poetry or rhetoric. Keywords: epistemology, metaphor, analogy, metaphilosophy, foundations, coherence.

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)

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.

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

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)

Choosing the right plan is often choosing the more coherent plan: but what is coherence? We argue that coherence-directed practical inference ought to be represented computationally. To that end, we advance a theory of deliberative coherence, and describe its implementation in a program modelled on Thagard's ECHO. We explain how the theory can be tested and extended, and consider its bearing on instrumentalist accounts of practical rationality.

The role of emotion in human action has long been neglected in the philosophy of action. Some prevalent misconceptions of the nature of emotion are responsible for this neglect: emotions are irrational; emotions are passive; and emotions have only an insignificant impact on actions. In this paper we argue that these assumptions about the nature of emotion are problematic and that the neglect of emotion's place in theories of action is untenable. More positively, we argue on the basis of recent (...) research in cognitive neuroscience that emotions may significantly affect action generation as well as action execution and control. Moreover, emotions also play a crucial role in people's explanation of action. We conclude that the concept of emotion deserves a more distinctive and central place in philosophical theories of action. (shrink)

The book Model-Based Reasoning in Scientific Discovery, aims to explain how specific modeling practices employed by scientists are productive methods of ...

In this paper we present Drama, a distributed model of analogical mapping that integrates semantic and structural constraints on constructing analogies. Specifically, Drama uses holographic reduced representations (Plate, 1994), a distributed representation scheme, to model the effects of structure and meaning on human performance of analogical mapping. Drama is compared to three symbolic models of analogy (SME, Copycat, and ACME) and one partially distributed model (LISA). We describe Drama's performance on a number of example analogies and assess the model in (...) terms of neurological and psychological plausibility. We argue that Drama's successes are due largely to integrating structural and semantic constraints throughout the mapping process. We also claim that Drama is an existence proof of using distributed representations to model high‐level cognitive phenomena. (shrink)

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 ...

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)

Peter Achinstein (1990, 1991) analyses the scientific debate that took place in the eighteenth and nineteenth centuries concerning the nature of light. He offers a probabilistic account of the methods employed by both particle theorists and wave theorists, and rejects any analysis of this debate in terms of coherence. He characterizes coherence through reference to William Whewell's writings concerning how "consilience of inductions" establishes an acceptable theory (Whewell, 1847) . Achinstein rejects this analysis because of its vagueness and lack of (...) reference to empirical data, concluding that coherence is insufficient to account for the belief change that took place during the wave-particle debate. (shrink)

The incredible achievements of modern scientific theories lead most of us to embrace scientific realism: the view that our best theories offer us at least roughly accurate descriptions of otherwise inaccessible parts of the world like genes, atoms, and the big bang. In Exceeding Our Grasp, Stanford argues that careful attention to the history of scientific investigation invites a challenge to this view that is not well represented in contemporary debates about the nature of the scientific enterprise. The historical record (...) of scientific inquiry, Stanford suggests, is characterized by what he calls the problem of unconceived alternatives. Past scientists have routinely failed even to conceive of alternatives to their own theories and lines of theoretical investigation, alternatives that were both well-confirmed by the evidence available at the time and sufficiently serious as to be ultimately accepted by later scientific communities. Stanford supports this claim with a detailed investigation of the mid-to-late 19th century theories of inheritance and generation proposed in turn by Charles Darwin, Francis Galton, and August Weismann. He goes on to argue that this historical pattern strongly suggests that there are equally well-confirmed and scientifically serious alternatives to our own best theories that remain currently unconceived. Moreover, this challenge is more serious than those rooted in either the so-called pessimistic induction or the underdetermination of theories by evidence, in part because existing realist responses to these latter challenges offer no relief from the problem of unconceived alternatives itself. Stanford concludes by investigating what positive account of the spectacularly successful edifice of modern theoretical science remains open to us if we accept that our best scientific theories are powerful conceptual tools for accomplishing our practical goals, but abandon the view that the descriptions of the world around us that they offer are therefore even probably or approximately true. (shrink)

The place of the emotions among the passions -- The analytic of the emotions I -- The analytic of the emotions II -- The dialectic of the emotions -- Pride, arrogance, and humility -- Shame, embarrassment, and guilt -- Envy -- Jealousy -- Anger -- Love -- Friendship -- Sympathy and empathy.

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

We contend that empathy is best viewed as a kind of analogical thinking of the sort described in the multiconstraint theory of analogy proposed by Keith Holyoak and Paul Thagard (1995). Our account of empathy reveals the Theory-theory/Simulation theory debate to be based on a false assumption and formulated in terms too simple to capture the nature of mental state ascription. Empathy is always simulation, but may simultaneously include theory-application. By properly specifying the analogical processes of empathy and their constraints, (...) we are able to show how the amount of theory needed to empathize is determined. (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)

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)

Recent theorizing about the nature of the cognitive impairment in autism suggests that autistic individuals display abnormally weak central coherence, the capacity to integrate information in order to make sense of one’s environment. Our article shows the relevance of computational models of coherence to the understanding of weak central coherence. Using a theory of coherence as constraint satisfaction, we show how weak coherence can be simulated ina a connectionist network that has unusually high inhibition compared to excitation. This connectionist model (...) simulates autistic behaviour on both the false belief task and the homograph task. (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.