Summary The paper presents a technical analysis of the notion of analogy by means of the notion of conceptual similarity (the inverse of distance). The main idea is to elucidate the analogy (similarity) between predicates (properties) in terms of the higher-order predicates they share or fail to share. The notions of predicate-similarity and theory-similarity (defined as the inverse of theory-distance) are then combined to give an analysis of the analogy between conceptual systems.

According to the traditional requirement, formulated by William Whewell in his account of the “consilience of inductions” in 1840, a scientific hypothesis should have unifying power in the sense that it explains and predicts several mutually independent phenomena. Variants of this notion of consilience or unification include deductive, inductive, and approximate systematization. Inference from surprising phenomena to their theoretical explanations was called abduction by Charles Peirce. As a unifying theory is independently testable by new kinds of phenomena, it should also (...) receive confirmation from its empirical success. The study of the prospects of probabilistic Bayesianism to motivate this kind of criterion for abductive confirmation is shown to lead to two quite distinct conceptions of unification. (shrink)

A Bayesian account of the virtue of unification is given. On this account, the ability of a theory to unify disparate phenomena consists in the ability of the theory to render such phenomena informationally relevant to each other. It is shown that such ability contributes to the evidential support of the theory, and hence that preference for theories that unify the phenomena need not, on a Bayesian account, be built into the prior probabilities of theories.

I argue that non-epistemic values are necessarily embedded in the measure of evidential strength of contrastive evidence. When evidence is contrastive, evidence is stronger the more it favours a hypothesis over a set of plausible, mutually exclusive alternative hypotheses. In such a contrastive epistemic setting, evidence has an effect not only on a particular hypothesis, but on the whole probability distribution over the set of alternative hypotheses. A natural way of analysing the incremental impact of new evidence on a set (...) of alternative hypotheses is in terms of uncertainty or ‘entropy’ reduction. There is no unique single measure of uncertainty/entropy, however, and, consequently, no single unique measure of uncertainty reduction. Finally, I argue that the ‘right’ measure of entropy reduction, and hence of evidential strength, depends on the pragmatic context and non-epistemic values. (shrink)

Measures of theory-Distance are defined for theories formalizable within first-Order predicate logic by using distributive normal forms. The account is applied to give measures of verisimilitude.

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)

Many generic sentences express stable inductive generalizations. Stable inductive generalizations are typically true for a causal reason. In this paper we investigate to what extent this is also the case for the generalizations expressed by generic sentences. More in particular, we discuss the possibility that many generic sentences of the form ‘ks have feature e’ are true because kind k have the causal power to ‘produce’ feature e. We will argue that such an analysis is quite close to a probabilistic (...) based analysis of generic sentences according to which ‘relatively many’ ks have feature e, and that, in fact, this latter type of analysis can be ‘grounded’ in terms of causal powers. We will argue, moreover, that the causal power analysis is sometimes preferred to a correlation-based analysis, because it takes the causal structure that gives rise to the probabilistic data into account. (shrink)

Derivational robustness may increase the degree to which various pieces of evidence indirectly confirm a robust result. There are two ways in which this increase may come about. First, if one can show that a result is robust, and that the various individual models used to derive it also have other confirmed results, these other results may indirectly confirm the robust result. Confirmation derives from the fact that data not known to bear on a result are shown to be relevant (...) when it is shown to be robust. Second, robustness may increase the degree to which the robust result is indirectly confirmed if it increases the weight with which existing evidence indirectly confirms it. This may happen when it strengthens the connection between the core and the robust result by showing that auxiliaries are not responsible for the result. (shrink)

In the methodology of scientific research programs (MSRP) there are important features on the problem of prediction, especially regarding novel facts. In his approach, Imre Lakatos proposed three different levels on prediction: aim, process, and assessment. Chapter 5 pays attention to the characterization of prediction in the methodology of research programs. Thus, it takes into account several features: (1) its pragmatic characterization, (2) the logical perspective as a proposition, (3) the epistemological component, (4) its role in the appraisal of research (...) programs, and (5) its place as a value for scientific research. -/- The notion of “novel facts” is highly relevant in his conception, where several aspects are involved: the directions of novel facts, the different kinds of novelty, and the transition from six possible options of “novel facts” to four choices. Thereafter, the prediction of novel facts as the criterion of appraisal is considered. On the one hand, this requires analyzing the theoretical, empirical, and heuristic possibilities of appraisal; and, on the other, whether there is an overemphasis on the role of prediction in methodology of scientific research programs. As a consequence, there is an analysis of Lakatos’ criterion of appraisal in MSRP and economics. (shrink)

Atocha Aliseda’s Abductive Reasoning (2006) gives a structural characterization of the “forward” explana-tory reasoning from a theory to observational data. This paper asks whether there are any interesting structural rules for the “backward” abductive reasoning from observations to explanatory theories. Ignoring statistical cases, a partial explication of abduction is converse deductive explanation: h is abducible from e iff h deductively explains e. This relation of abducibility trivially satisfies Converse Entailment (if h entails e, then h is abducible from e ), (...) but it does not generally satisfy Converse Consequence (if h is abducible from e and g entails h, then g is abducible from e ), since deductive explanation is not always transitive. (shrink)

This paper gives a critical evaluation of the philosophical presuppositions and implications of two current schools in the sociology of knowledge: the Strong Programme of Bloor and Barnes; and the Constructivism of Latour and Knorr-Cetina. Bloor's arguments for his externalist symmetry thesis (i.e., scientific beliefs must always be explained by social factors) are found to be incoherent or inconclusive. At best, they suggest a Weak Programme of the sociology of science: when theoretical preferences in a scientific community, SC, are first (...) internally explained by appealing to the evidence, e, and the standards or values, V, accepted in SC, then a sociologist may sometimes step in to explain why e and V were accepted in SC. Latour's story about the social construction of facts in scientific laboratories is found to be misleading or incredible. The idea that scientific reality is an artifact turns out to have some interesting affinities with classical pragmatism, instrumentalism, phenomenology, and internal realism. However, the constructivist account of theoretical entities in terms of negotiation and social consensus is less plausible than the alternative realist story which explains consensus by the preexistence of mind-independent real entities. The author concludes that critical scientific realism, developed with the concept of truthlikeness, is compatible with the thesis that scientific beliefs or knowledge claims may be relative to various types of cognitive and practical interests. However, the realist denies, with good reasons, the stronger type of relativism which takes reality and truth to be relative to persons, groups, or social interests. (shrink)

The present paper first shows that the validity of deductive-nomological (D-N) explanations (systematizations) depends in general on the interpretation context of the predicates involved in the explanation. Therefore, no logical-semantical model can be adequate. This problem is solved by relativisation of the validity criteria on both the confirmation context and the definition context of the premisses. Based upon this, a logical-pragmatical model of D-N explanation is developed. Thereby, especially explanations of laws and global explanations are taken into consideration, since these (...) can be regarded as prototypes of scientific explanation. (shrink)