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)

When someone is asked to speak his mind, it is sometimes possible for him to furnish what his utterance appears to have omitted. In such cases we might say that he had a mind to speak. Sometimes, however, the opposite is true. Asked to speak his mind, our speaker finds that he has no mind to speak. When it is possible to speak one's mind and when not is largely determined by the kinds of beings we are and by the (...) kinds of resources we are able to draw upon. In either case, not speaking one's mind is leaving something out whose articulation would or could matter for the purposes for which one was speaking in the first place. Inarticulation is no fleetingly contingent and peripheral phenomenon in human thinking and discourse. It is a substantial and dominant commonplace. In Part One I attempt to say something about what it is about the human agent that makes inarticulateness so rife. In Part Two, I consider various strategies for making the unarticulated explicit, and certain constraints on such processes. I shall suggest, among other things, that standard treatments of enthymematic reconstruction are fundamentally misconceived. (shrink)

Abduction was first introduced in the epistemological context of scientific discovery. It was more recently analyzed in artificial intelligence, especially with respect to diagnosis analysis or ordinary reasoning. These two fields share a common view of abduction as a general process of hypotheses formation. More precisely, abduction is conceived as a kind of reverse explanation where a hypothesis H can be abduced from events E if H is a good explanation of E. The paper surveys four known schemes for abduction (...) that can be used in both fields. Its first contribution is a taxonomy of these schemes according to a common semantic framework based on belief revision. Its second contribution is to produce, for each non-trivial scheme, a representation theorem linking its semantic framework to a set of postulates. Its third contribution is to present semantic and axiomatic arguments in favor of one of these schemes, ordered abduction, which has never been vindicated in the literature. (shrink)

This work proposes an understanding of deductive, default and abductive reasoning as different instances of the same phenomenon: epistemic dynamics. It discusses the main intuitions behind each one of these reasoning processes, and suggest how they can be understood as different epistemic actions that modify an agent’s knowledge and/or beliefs in a different way, making formal the discussion with the use of the dynamic epistemic logic framework. The ideas in this paper put the studied processes under the same umbrella, thus (...) highlighting their relationship and allowing a better understanding of how they interact together. (shrink)

The roles of abductive inference in dynamic heuristics allows scientific methodologies to test novel explanations for the world’s ways. Deliberate reasoning often follows abductive patterns, as well as patterns dominated by deduction and induction, but complex mixtures of these three modes of inference are crucial for scientific explanation. All possible mixed inferences are formulated and categorized using a novel typology and nomenclature. Twenty five possible combinations among abduction, induction, and deduction are assembled and analyzed in order of complexity. There are (...) five primary categories for sorting these inferential procedures: fallacies, non-scientific procedures, quasi-scientific procedures, scientific procedures, and scientific heuristics. (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)

This paper explores the question of what logic is not. It argues against the wide spread assumptions that logic is: a model of reason; a model of correct reason; the laws of thought, or indeed is related to reason at all such that the essential nature of the two are crucially or essentially co-illustrative. I note that due to such assumptions, our current understanding of the nature of logic itself is thoroughly entangled with the nature of reason. I show that (...) most arguments for the presence of any sort of essential re- lationship between logic and reason face intractable problems and demands, and fall well short of addressing them. These arguments include those for the notion that logic is normative for reason (or that logic and correct reason are in some way the same thing), that logic is some sort of description of correct reason and that logic is an abstracted or idealised version of correct reason. A strong version of logical realism is put forward as an alternative view, and is briefly explored. (shrink)

Abduction is considered the most powerful, but also the most controversially discussed type of inference. Based on an analysis of Peirce’s retroduction, Lipton’s Inference to the Best Explanation and other theories, a new theory of abduction is proposed. It considers abduction not as intrinsically explanatory but as intrinsically conditional: for a given fact, abduction allows one to infer a fact that implies it. There are three types of abduction: Selective abduction selects an already known conditional whose consequent is the given (...) fact and infers that its antecedent is true. Conditional-creative abduction creates a new conditional in which the given fact is the consequent and a defined fact is the antecedent that implies the given fact. Propositional-conditional-creative abduction assumes that the given fact is implied by a hitherto undefined fact and thus creates a new conditional with a new proposition as antecedent. The execution of abductive inferences is specified by theory-specific patterns. Each pattern consists of a set of rules for both generating and justifying abductive conclusions and covers the complete inference process. Consequently, abductive inferences can be formalised iff the whole pattern can be formalised. The empirical consistency of the proposed theory is demonstrated by a case study of Semmelweis' research on puerperal fever. (shrink)

There are at least twelve major virtues of good theories: evidential accuracy, causal adequacy, explanatory depth, internal consistency, internal coherence, universal coherence, beauty, simplicity, unification, durability, fruitfulness, and applicability. These virtues are best classified into four classes: evidential, coherential, aesthetic, and diachronic. Each virtue class contains at least three virtues that sequentially follow a repeating pattern of progressive disclosure and expansion. Systematizing the theoretical virtues in this manner clarifies each virtue and suggests how they might have a coordinated and cumulative (...) role in theory formation and evaluation across the disciplines—with allowance for discipline specific modification. An informal and flexible logic of theory choice is in the making here. Evidential accuracy, according to my systematization, is not a largely isolated trait of good theories, as some have made it out to be. Rather, it bears multifaceted relationships, constituting significant epistemic entanglements, with other theoretical virtues. (shrink)

In Artificial Intelligence, abduction is often formalized in first-order logic. In this article, we focus on the problem of identifying equivalence of two abductive theories represented in first-order logic. To this end, two definitions of equivalence are given for abduction. Explainable equivalence requires that two abductive theories have the same explainability for any observation. On the other hand, explanatory equivalence guarantees that any observation has exactly the same explanations in each abductive theory. Explanatory equivalence is a stronger notion than explainable (...) equivalence. In first-order logic, explainable equivalence can be veri.ed by the notion of extensional equivalence in default theories, while explanatory equivalence reduces to logical equivalence between background theories. We also show the complexity results for abductive equivalence. (shrink)

This paper defines in a formal and computational way the notion of ‘consilience’, a term introduced by Whewell in 1847 for the evaluation of scientific theories. Informally, as has been used to date, a model or theory is ‘consilient’ if it is predictive, explanatory and unifies the evide-nce. Centred in a constructive framework, where new terms can be intro-duced, we essay a formalisation of the idea of unification based on the avoidance of ‘sepa-ration’. However, it is soon manifest that this (...) classical approach is vulnerable to the introduction of fantastic concepts to unify disparate sub-theories. Our second approach is constructed by using a detailed evaluation of the relationship between the theory and the evid-ence by means of reinforcement propagation. With the use of reinfor-cement, fantastic concepts can be better detected and the role of con-silience for theory construction and revision can be specialised for dif-ferent inference mechanisms like explanatory induction, abduction, deduc-tion and analogy. (shrink)

En este trabajo argumento a favor de la idea de que una explicación científica es una respuesta a una pregunta, aunque no necesariamente a una pregunta-por-qué. Esto no quiere decir que las preguntas-por-qué no sean elementos fundamentales de toda investigación científica: su importancia radica en que son capaces de organizar y sistematizar un conjunto dado de creencias. Para justificar esta afirmación, comienzo por identificar tres estadios básicos en los cuales pueden surgir preguntas-por-qué, y luego procedo a caracterizar su estructura. Muestro (...) finalmente cómo usar este análisis para elucidar la noción de poder de unificación de hipótesis rivales. Entiendo que esta última noción, a su vez, constituye uno de los criterios que debemos considerar a la hora de evaluar cuál de dichas hipótesis rivales es la mejor explicación disponible, comparativamente hablando. In this paper I take scientific explanations to be answers to questions, though not necessarily to why-questions. This, however, is not meant to imply that why-questions are not fundamental in their own peculiar way. As I understand it, why-questions are crucial elements in any research process because they are able to organize and systematize an agent's belief set. In order to justify my claim I start by identifying three basic stages in which whyquestions can arise, and then I proceed to characterize their structure. I also show how to use this analysis to elucidate the notion of comparative unification power of rival hypotheses. The notion of comparative unification power, in turn, can be thought of as one of the criteria that we should take into account at the time of assessing which of such rival hypotheses is the best explanation available, comparatively speaking. (shrink)