This book examines the philosophical conception of abductive reasoning as developed by Charles S. Peirce, the founder of American pragmatism. It explores the historical and systematic connections of Peirce's original ideas and debates about their interpretations. Abduction is understood in a broad sense which covers the discovery and pursuit of hypotheses and inference to the best explanation. The analysis presents fresh insights into this notion of reasoning, which derives from effects to causes or from surprising observations to explanatory theories. The (...) author outlines some logical and AI approaches to abduction as well as studies various kinds of inverse problems in astronomy, physics, medicine, biology, and human sciences to provide examples of retroductions and abductions. The discussion covers also everyday examples with the implication of this notion in detective stories, one of Peirce’s own favorite themes. The author uses Bayesian probabilities to argue that explanatory abduction is a method of confirmation. He uses his own account of truth approximation to reformulate abduction as inference which leads to the truthlikeness of its conclusion. This allows a powerful abductive defense of scientific realism. This up-to-date survey and defense of the Peircean view of abduction may very well help researchers, students, and philosophers better understand the logic of truth-seeking. (shrink)

Recently, some philosophers of science (e.g., Gürol Irzik, Michael Friedman) have challenged the ‘received view’ on the relationship between Rudolf Carnap and Thomas Kuhn, suggesting that there is a close affinity (rather than opposition) between their philosophical views. In support of this argument, these authors cite Carnap and Kuhn’s similar views on incommensurability, theory-choice, and scientific revolutions. Against this revisionist view, I argue that the philosophical relationship between Carnap and Kuhn should be regarded as opposed rather than complementary. In particular, (...) I argue that a consideration of the fundamentally disparate nature of the broader philosophical projects of Carnap (logic of science) and Kuhn (providing a theory of scientific revolutions)renders the alleged similarities between their views superficial in comparison to their fundamental differences. In defense of the received view, I suggest that Carnap and Kuhn are model representatives of two contrasting styles of doing philosophy of science, viz., logical analysis and historical analysis respectively. This analysis clarifies the role played by Kuhn’s Structure of Scientific Revolutions in the demise of logical empiricism in the second half of the twentieth-century. (shrink)

The formal definition of species as explanatory hypotheses presented by Fitzhugh is emended. A species is an explanatory account of the occurrences of the same character among gonochoristic or cross-fertilizing hermaphroditic individuals by way of character origin and subsequent fixation during tokogeny. In addition to species, biological systematics also employs hypotheses that are ontogenetic, tokogenetic, intraspecific, and phylogenetic, each of which provides explanatory hypotheses for distinctly different classes of causal questions. It is suggested that species hypotheses can not be applied (...) to organisms with obligate asexual, parthenogenetic, and self-fertilizing modes of reproduction. Hypotheses explaining shared characters among such organisms are, instead, strictly phylogenetic. Several implications of this emended definition are examined, especially the relations between species, intraspecific, and phylogenetic hypotheses, as well as the limitations of species names to be applied to temporally different characters within populations. (shrink)

Bayesian probability is normally defined over a fixed language or eventspace. But in practice language is susceptible to change, and thequestion naturally arises as to how Bayesian degrees of belief shouldchange as language changes. I argue here that this question poses aserious challenge to Bayesianism. The Bayesian may be able to meet thischallenge however, and I outline a practical method for changing degreesof belief over changes in finite propositional languages.

The relationship between machine learning and the philosophy of science can be classed as a dynamic interaction: a mutually beneficial connection between two autonomous fields that changes direction over time. I discuss the nature of this interaction and give a case study highlighting interactions between research on Bayesian networks in machine learning and research on causality and probability in the philosophy of science.

Since at least the 1938 publication of Hans Reichenbach’s Experience and Predication , there has been widespread agreement that, when discussing the beliefs that people have, it is important to distinguish contexts of discovery and contexts of justification. Traditionally, when one conflates the two contexts, the result is a “genetic fallacy”. This paper examines genealogical critiques and addresses the question of whether such critiques are fallacious and, if so, whether this vitiates their usefulness. The paper concludes that while there may (...) be one or more senses in which genealogical critiques are fallacious, this does not vitiate their value. (shrink)

In this paper I evaluate the soundness of the prototype paradigm, in particular its basic assumption that there are pan-human psychological essences or core meanings that refer to basic-level natural kinds, explaining why, on the whole, human communication and learning are successful. Instead I argue that there are no particular pan-human basic elements for thought, meaning and cognition, neither prototypes, nor otherwise. To illuminate my view I draw on examples from anthropology. More generally I argue that the prototype paradigm exemplifies (...) two assumptions that dominate cognitive science: (1) If human beings use words they mean something particular and what they mean can be discovered by scientific methods. (2) There is a fixed number of domains of categorization, each made up of a fixed number of basic categories. I suggest that these two assumptions lead to Brave New World. (shrink)

En los inicios del siglo XXI está desarrollándose una e-ciencia, una ciencia electrónica y altamente computarizada que exige un replanteamiento sobre la epistemología científica. A través del ejemplo de la Bioinformática y las Biotecnologías, el autor muestra algunas características de esta nueva e-ciencia e indica algunos de los problemas con los que deben enfrentarse los filósofos de la ciencia contemporáneos. Right at the beginning of the 21st century an e-Science is emerging, a highly computerized electronic science which demands a new (...) way of understanding scientific epistemology. Through Bioinformatics and Biotechnologies, the author analyzes some of the characteristics of this new e-Science and shows several problems which contemporary philosophers of science must face. (shrink)

According to Thagard, the behavior of practitioners of a field may also be used for demarcation between science and pseudoscience due to its social dimension in addition to the epistemic one. I defended the tendency of pseudoscientists to commit fallacies, and the number of fallacies they commit can be a secondary tool for demarcation problem and this tool is consistent with Thagardian approach. In this paper, I selected the astrology as the case and I revealed nine types of logical fallacies (...) frequently committed by astrologers while introducing their field and/or defending their claims against the scientific inquiries and refutation efforts. I also argued that recognizing these fallacies may help the audience to demarcate between the scientific and the pseudoscientific arguments. (shrink)

The demarcation of pseudoscience has been one of the most important philosophical tasks since the 1960s. During the 1980s, an atmosphere of defeatism started to spread among philosophers of science, some of them claimed the failure of the demarcation project. I defend that the more auspicious approach to the problem might be through the intellectual character of epistemic agents, i.e., from the point of view of vice epistemology. Unfortunately, common lists of undesirable character features are usually based on a priori (...) reasoning, and therefore might be considered artificial or too vague. When we base our position on contemporary behavioural sciences, we can see that the epistemic character of believers in pseudoscience is for the most part determined by two related factors. Firstly, these epistemic agents show a higher level of cognitive laziness. By this I mean an inability or unwillingness to engage in reflective thinking and a reluctance to account for counterevidence. Secondly, they yield more easily to metacognitive overconfidence. This can be broadly understood as so-called “knowledge illusion”, the inability to recognize one’s own intellectual limits. The deficiency usually stems from a misunderstanding of the division of cognitive labour and of the agent’s role in epistemic society. I find the proposed epistemological approach to pseudoscience crucial. Only if we understand the descriptive aspects of the problem, can we think of normative solutions to it. (shrink)

The paper explicates unique events and investigates their epistemology. Explications of unique events as individuated, different, and emergent are philosophically uninteresting. Unique events are topics of why-questions that radically underdetermine all their potential explanations. Uniqueness that is relative to a level of scientific development is differentiated from absolute uniqueness. Science eliminates relative uniqueness by discovery of recurrence of events and properties, falsification of assumptions of why-questions, and methodological simplification e.g. by explanatory methodological reduction. Finally, an overview of contemporary philosophical disputes (...) that hinge on issues of uniqueness emphasizes its philosophical significance. (shrink)

In this paper we show that any reasoning process in which conclusions can be both fallible and corrigible can be formalized in terms of two approaches: (i) syntactically, with the use of defeasible reasoning, according to which reasoning consists in the construction and assessment of arguments for and against a given claim, and (ii) semantically, with the use of partial structures, which allow for the representation of less than conclusive information. We are particularly interested in the formalization of scientific reasoning, (...) along the lines traced by Lakatos’ methodology of scientific research programs. We show how current debates in cosmology could be put into this framework, shedding light on a very controversial topic. (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)

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)

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)

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)

Darwin’s theory of evolution by natural selection is central to modern biology, but is resisted by many people. This paper discusses the major psychological obstacles to accepting Darwin’s theory. Cognitive obstacles to adopting evolution by natural selection include conceptual difficulties, methodological issues, and coherence problems that derive from the intuitiveness of alternative theories. The main emotional obstacles to accepting evolution are its apparent conflict with valued beliefs about God, souls, and morality. We draw on the philosophy of science and on (...) a psychological theory of cognitive and emotional belief revision to make suggestions about what can be done to improve acceptance of Darwinian ideas. (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.

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)

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)

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 article is a response to Elijah Millgram's argument that my characterization of coherence as constraint satisfaction is inadequate for philosophical purposes because it provides no guarantee that the most coherent theory available will be true. I argue that the constraint satisfaction account of coherence satisfies the philosophical, computational, and psychological prerequisites for the development of epistemological and ethical theories.

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)

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.

This article provides a historical, philosophical, and psychological analysis of the recent discovery that reoviruses are oncolytic, capable of infecting and destroying many kinds of cancer cells. After describing Patrick Lee's very indirect path to this discovery, I discuss the implications of this case for understanding the nature of scientific discovery, including the economy of research, anomaly recognition, hypothesis formation, and the role of emotion in scientific thinking. Lee's discoveries involved a combination of serendipity, abductive and deductive inference, and emotional (...) cognition. (shrink)

In adversarial problem solving (APS), one must anticipate, understand and counteract the actions of an opponent. Military strategy, business, and game playing all require an agent to construct a model of an opponent that includes the opponent's model of the agent. The cognitive mechanisms required for such modeling include deduction, analogy, inductive generalization, and the formation and evaluation of explanatory hypotheses. Explanatory coherence theory captures part of what is involved in APS, particularly in cases involving deception.

Currently there is hardly any connection between philosophy of science and Artificial Intelligence research. We argue that both fields can benefit from each other. As an example of this mutual benefit we discuss the relation between Inductive-Statistical Reasoning and Default Logic. One of the main topics in AI research is the study of common-sense reasoning with incomplete information. Default logic is especially developed to formalise this type of reasoning. We show that there is a striking resemblance between inductive-statistical reasoning and (...) default logic. A central theme in the logical positivist study of inductive-statistical reasoning such as Hempels Criterion of Maximal Specificity turns out to be equally important in default logic. We also discuss to what extent the relevance of the results of Logical Positivism to AI research could contribute to a reevaluation of Logical Positivism in general. (shrink)

In recent years there has been a great deal of discussion about the prospects of developing a “naturalized epistemology,” though different authors tend to interpret this label in quite different ways.1 One goal of this paper is to sketch three projects that might lay claim to the “naturalized epistemology” label, and to argue that they are not all equally attractive. Indeed, I’ll maintain that the first of the three – the one I’ll attribute to Quine – is simply incoherent. There (...) is no way we could get what we want from an epistemological theory by pursuing the project Quine proposes. The second project on my list is a naturalized version of reliabilism. This project is not fatally flawed in the way that Quine’s is. However, it’s my contention that the sort of theory this project would yield is much less interesting than might at first be thought. (shrink)

The paper proposes a synthesis between human scientists and artificial representation learning models as a way of augmenting epistemic warrants of realist theories against various anti-realist attempts. Towards this end, the paper fleshes out unconceived alternatives not as a critique of scientific realism but rather a reinforcement, as it rejects the retrospective interpretations of scientific progress, which brought about the problem of alternatives in the first place. By utilising adversarial machine learning, the synthesis explores possibility spaces of available evidence for (...) unconceived alternatives providing modal knowledge of what is possible therein. As a result, the epistemic warrant of synthesised realist theories should emerge bolstered as the underdetermination by available evidence gets reduced. While shifting the realist commitment away from theoretical artefacts towards modalities of the possibility spaces, the synthesis comes out as a kind of perspectival modelling. (shrink)

Naturalistic epistemologists frequently assume that their aim is to identify generalities (i.e. general laws) about the effectiveness of particular reasoning processes and methods. This paper argues that the search for this kind of generality fails. Work that has been done thus far to identify generalities (e.g. by Goldman, Kitcher and Thagard) overlooks both the complexity of reasoning and the relativity of assessments to particular contexts (domain, stage and goal of inquiry). Examples of human reasoning which show both complexity and contextuality (...) are given. The paper concludes with a discussion of the kind of multivariate model of reasoning that naturalistic epistemologists can use to evaluate processes and methods for specific domains. (shrink)

The logical empiricists held that an analogical hypothesis does not gain any acceptability from the analogy on which it is founded. On this view, the acceptability of a hypothesis cannot be discounted by criticizing the foundational analogy. Yet scientists commonly appear to level exactly this sort of criticism. If scientists are able to discount the acceptability of analogical hypotheses in this way, then the logical empiricist view is mistaken. I analyze four forms of analogy counterargument, disanalogy, misanalogy, counteranalogy, and false (...) analogy, with examples from the debate over the asteroid impact hypothesis. These counterarguments do address the acceptability of analogical hypotheses, indicating that analogies can confer acceptability, confirmation notwithstanding. 1 Introduction 2 The asteroid impact hypothesis 3 Analogy counterarguments 3.1 Disanalogy 3.2 Misanalogy 3.3 Counteranalogy 3.4 False analogy 4 Acceptability 5 Conclusions. (shrink)

This article describes abductions as special patterns of inference to the best explanation whose structure determines a particularly promising abductive conjecture and thus serves as an abductive search strategy. A classification of different patterns of abduction is provided which intends to be as complete as possible. An important distinction is that between selective abductions, which choose an optimal candidate from given multitude of possible explanations, and creative abductions, which introduce new theoretical models or concepts. While selective abduction has dominated the (...) literature, creative abductions are rarely discussed, although they are essential in science. The article introduces several kinds of creative abductions, such as theoretical model abduction, common cause abduction and statistical factor analysis, and illustrates them by various real case examples. It is suggested to demarcate scientifically fruitful abductions from purely speculative abductions by the criterion of causal unification. (shrink)