This paper defends an account of explanatory reasoning generally, and inference to the best explanation in particular, according to which it first and foremost justifies pursuing hypotheses rather than accepting them as true. This side-steps the problem of why better explanations should be more likely to be true. I argue that this account faces no analogous problems. I propose an account of justification for pursuit and show how this provides a simple and straightforward connection between explanatoriness and justification for (...) pursuit. (shrink)

What kind of thing is a reason for action? Are reasons for action subjective states of the agent, such as desires and/or beliefs? Or are they, rather, objective features of situations that favor certain actions? The suggestion offered in this article is that neither strategy satisfies. What is needed is a third category for classifying reasons which makes them out to be neither purely subjective nor purely objective. In brief: a reason for action is a feature of the (...) situation that matters to the agent. On this proposal, subjective states of the agent are indeed indispensable in characterizing reasons for action. Precisely which set of situational features matter to an agent—precisely what shape the agent experiences the situation as having—depends on the agent's psychological makeup. Those features themselves are not psychological states, however, and it is precisely those features that constitute the agent's reasons for action. (shrink)

When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be robust. This paper investigates the logic of such "robustness analysis" [RA]. The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal explications of such diversity are unsatisfactory. I propose a (...) unified, explanatory account of diversity in RAs. The resulting account is, I argue, truer to actual cases of RA in science; moreover, this account affords us a helpful, new foothold on the logic undergirding RAs. (shrink)

In his recent book, John Norton has created a theory of inference to the best explanation, within the context of his "material theory of induction". I apply it to the problem of scientific explanations that are false: if we want the theories in our explanations to be true, then why do historians and scientists often say that false theories explained phenomena? I also defend Norton's theory against some possible objections.

Boris Kment takes a new approach to the study of modality that emphasises the origin of modal notions in everyday thought. He argues that the concepts of necessity and possibility originate in counterfactual reasoning, which allows us to investigate explanatory connections. Contrary to accepted views, explanation is more fundamental than modality.

Recent work on inference to the best explanation has come to an impasse regarding the proper way to coordinate the theoretical virtues in explanatory inference with probabilistic confirmation theory, and in particular with aspects of Bayes's Theorem. I argue that the theoretical virtues are best conceived heuristically and that such a conception gives us the resources to explicate the virtues in terms of ceteris paribus theorems. Contrary to some Bayesians, this is not equivalent to identifying the virtues with likelihoods (...) or priors per se; the virtues may be more accessible epistemically than likelihoods or priors. I then prove a ceteris paribus theorem regarding theoretical consilience, use it to correct a recent application of Reichenbach's common cause principle, and apply it to a test case of scientific reasoning. Explanation and confirmation The heuristic conception of theoretical virtues Abduction and the accessibility of explanatory power Evidential and theoretical consilience A test case: gravitational lensing Conclusion Thus natural science appears completely to lose from sight the large and general questions; but all the more splendid is the success when, groping in the thicket of special questions, we suddenly find a small opening that allows a hitherto undreamt of outlook on the whole. (L. Boltzmann, Theoretical Physics and Philosophical Problems). (shrink)

ABSTRACT When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be ‘robust’. This article investigates the logic of such ‘robustness analysis’. The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal explications of such diversity are unsatisfactory. I propose a (...) unified, explanatory account of diversity in RAs. The resulting account is, I argue, truer to actual cases of RA in science; moreover, this account affords us a helpful new foothold on the logic undergirding RAs. 1Robustness Analysis in Science 2RA Diversity and Independence 2.1Unconditional probabilistic independence 2.2Reliability independence 2.3Confirmational and conditional independence 2.4Partial independence? 3Robustness Analysis as Explanatory Reasoning 3.1Explanatorily discriminating means of detection 3.2The logic of robustness analysis 3.2.1Mutually exclusive competitors 3.2.2Consistent epistemic competitors 4Conclusion Appendix. (shrink)

In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in Section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In Section 3, I argue that these methodological claims are in tension with a (...) prominent account of scientific method, often called “Inference to the Best Explanation”. Later on, in Section 3, I consider an argument against IBE that will be congenial to proponents of Big Data, namely, the argument due to Roche and Sober Analysis, 73:659–668, that “explanatoriness is evidentially irrelevant.” This argument is based on Bayesianism, one of the most prominent general accounts of theory-confirmation. In Section 4, I consider some extant responses to this argument, especially that of Climenhaga Philosophy of Science, 84:359–368,. In Section 5, I argue that Roche and Sober’s argument does not show that explanatory reasoning is dispensable. In Section 6, I argue that there is good reason to think explanatory reasoning will continue to prove indispensable in scientific practice. Drawing on Cicero’s oft-neglected De Divinatione, I formulate what I call the “Ciceronian Causal-nomological Requirement”, which states, roughly, that causal-nomological knowledge is essential for relying on correlations in predictive inference. I defend a version of the CCR by appealing to the challenge of “spurious correlations,” chance correlations which we should not rely upon for predictive inference. In Section 7, I offer some concluding remarks. (shrink)

A review of Boris Kment, Modality and Explanatory Reasoning.

The aim of Modality and Explanatory Reasoning (MER) is to shed light on metaphysical necessity and the broader class of modal properties to which it belongs. This topic is approached with two goals: to develop a new and reductive analysis of modality, and to understand the purpose and origin of modal thought. I argue that a proper understanding of modality requires us to reconceptualize its relationship to causation and other forms of explanation such as grounding, a relation that connects (...) metaphysically fundamental facts to non-fundamental ones. While many philosophers have tried to give modal analyses of causation and explanation, often in counterfactual terms, I argue that we obtain a more plausible, explanatorily powerful and unified theory if we regard explanation as more fundamental than modality. The function of modal thought is to facilitate a common type of thought experiment – counterfactual reasoning – that allows us to investigate explanatory connections and which is closely related to the controlled experiments of empirical science. Necessity is defined in terms of explanation, and modal facts often reflect underlying facts about explanatory relationships. The study of modal facts is important for philosophy not because these facts are of much metaphysical interest in their own right, but largely because they provide evidence about explanatory connections. (shrink)

The aim of Modality and Explanatory Reasoning (MER) is to shed light on metaphysical necessity and the broader class of modal properties to which it belongs. This topic is approached with two goals: to develop a new and reductive analysis of modality, and to understand the purpose and origin of modal thought. I argue that a proper understanding of modality requires us to reconceptualize its relationship to causation and other forms of explanation such as grounding, a relation that connects (...) metaphysically fundamental facts to non-fundamental ones. While many philosophers have tried to give modal analyses of causation and explanation, often in counterfactual terms, I argue that we obtain a more plausible, explanatorily powerful and unified theory if we regard explanation as more fundamental than modality. The function of modal thought is to facilitate a common type of thought experiment—counterfactual reasoning—that allows us to investigate explanatory connections and which is closely related to the controlled experiments of empirical science. Necessity is defined in terms of explanation, and modal facts often reflect underlying facts about explanatory relationships. The study of modal facts is important for philosophy not because these facts are of much metaphysical interest in their own right, but largely because they provide evidence about explanatory connections. (shrink)

This chapter examines issues surrounding inference to the best explanation, its justification, and its role in different arguments for scientific realism, as well as more general issues concerning explanations’ ontological commitments. Defending the reliability of inference to the best explanation has been a central plank in various realist arguments, and realists have drawn various ontological conclusions from the premise that a given scientific explanation best explains some phenomenon. This chapter stresses the importance of thinking carefully about the nature of explanation (...) in connection with evaluating realists’ appeals to explanatory reasoning and inference to the best explanation. (shrink)

In this critical notice of Kment's _Modality and Explanatory Reasoning_, we focus on Kment’s arguments for impossible worlds and on a key part of his discussion of the interactions between modality and explanation – the analogy that he draws between scientific and metaphysical explanation.

In this new explanationist account of epistemic justification, Poston argues that the explanatory virtues provide all the materials necessary for a plausible account of justified belief. There are no purely autonomous reasons. Rather reasons occur only within an explanatory coherent set of beliefs.

We explore the possibilities that dynamic epistemic logic offers to model abductive reasoning. We show that many of the problems with formal approaches to abduction based on classical logic can be solved when considering an epistemic agent that reasons and acts.Exploramos las posibilidades que ofrece la lógica epistémica dinámica para modelar el razonamiento abductivo. Mostramos que muchos de los problemas que encuentran los tratamientos formales de la abducción basados en lógica clásica pueden ser resueltos al considerar un agente epistémico (...) que razona y actúa. (shrink)

Joseph Raz accepts the ‘normative/explanatory nexus’ which states, roughly, that ‘necessarily normative reasons can explain the actions, beliefs, and the like of rational agents’ (From Normativity to Responsibility, 34). I agree with this rough statement, but I disagree with Raz on the details of the nexus. I further argue that, once we see the correct version of the nexus and the reasons why it is true, we must accept an account of the nature of normative reasons (...) that goes against another central commitment of Raz's. Specifically, we must reject Raz's view that ultimately, normative reasons for action are provided by the value of the relevant action. Instead, what it is to be a normative reason is to be a premise in good reasoning, of a certain sort. Actions supported by normative reasons may be valuable in some way, but it is not ultimately because of their value that we have normative reasons to perform them. I also briefly gesture at why the resulting type of ‘good reasoning’ view of normative reasons offers a more unified and explanatorily satisfying view of normative reasons for action, belief, and other responses than Raz's view. (shrink)

The question of how judgments of explanatory value inform probabilistic inference is well studied within psychology and philosophy. Less studied are the questions: How does probabilistic information affect judgments of explanatory value? Does probabilistic information take precedence over causal information in determining explanatory judgments? To answer these questions, we conducted two experimental studies. In Study 1, we found that probabilistic information had a negligible impact on explanatory judgments of event-types with a potentially unlimited number of available, (...) alternative explanations; causal credibility was the main determinant of explanatory value. In Study 2, we found that, for event-token explanations with a definite set of candidate alternatives, probabilistic information strongly affected judgments of explanatory value. In the light of these findings, we reassess under which circumstances explanatory inference is probabilistically sound. (shrink)

We introduce a “reason-based” framework for explaining and predicting individual choices. It captures the idea that a decision-maker focuses on some but not all properties of the options and chooses an option whose motivationally salient properties he/she most prefers. Reason-based explanations allow us to distinguish between two kinds of context-dependent choice: the motivationally salient properties may (i) vary across choice contexts, and (ii) include not only “intrinsic” properties of the options, but also “context-related” properties. Our framework can accommodate boundedly rational (...) and sophisticatedly rational choice. Since properties can be recombined in new ways, it also offers resources for predicting choices in unobserved contexts. (shrink)

I present an explanatory argument for the reasons-first view: It is superior to knowledge-first views in particular in that it can both explain the specific epistemic role of perception and account for the shape and extent of epistemic justification.

The relation between probabilistic and explanatory reasoning is a classical topic in philosophy of science. Most philosophical analyses are concerned with the compatibility of Inference to the Best Explanation with probabilistic, Bayesian inference, and the impact of explanatory considerations on the assignment of subjective probabilities. This paper reverses the question and asks how causal and explanatory considerations are affected by probabilistic information. We investigate how probabilistic information determines the explanatory value of a hypothesis, and in which (...) sense folk explanatory practice can be said to be rational. Our study identifies three main factors in reasoning about a explanatory hypothesis: cognitive salience, rational acceptability and logical entailment. This corresponds well to the variety of philosophical accounts of explanation. Moreover, we show that these factors are highly sensitive to manipulations of probabilistic information. This finding suggests that probabilistic reasoning is a crucial part of explanatory inferences, and it motivates new avenues of research in the debate about Inference to the Best Explanation and probabilistic measures of explanatory power. (shrink)

In this essay, I address an objection to inference to the best explanation due to Bas C. van Fraassen, according to which explanatory virtues cannot confirm a theory, since they make the theory more informative and thus less likely to be true given the probability axioms. I try to show that van Fraassen’s argument, once made precise, is deductively invalid, and that even an ampliative version of the argument (i) implies, absurdly, that no theory is confirmed by its fit (...) with empirical data; (ii) fails to account for confirmatory closure under deduction; and (iii) falsely presupposes that a theory and its sub-theories can be competing explanations. (shrink)

A thesis familiar by being as often disputed as defended has it that intentional action is action for a reason. The present paper contributes to the defence of a weaker version of it, namely: Acting with an intention or a purpose is acting (as things appear to one) for a reason.

Cognitivists about practical reason hold that we can explain why certain wide-scope requirements of practical rationality are true by appealing to certain epistemic requirements. Extant discussions of cognitivism focus solely on two claims. The first is the claim that intentions involve beliefs. The second is that whenever your intentions are incoherent in certain ways, you will be epistemically irrational. Even if the cognitivist successfully defends these claims, she still needs to show that they entail certain practical requirements. That is, she (...) has to show that the epistemic requirements explain the practical requirements. In this paper I argue that it is not plausible that the epistemic requirements explain the practical requirements. This shows that the cognitivists' project will fail even if we grant their controversial views about the relationship between the practical and epistemic. (shrink)

The paper investigates measures of explanatory power and how to define the inference schema “Inference to the Best Explanation”. It argues that these measures can also be used to quantify the systematic power of a hypothesis and the inference schema “Inference to the Best Systematization” is defined. It demonstrates that systematic power is a fruitful criterion for theory choice and IBS is truth-conducive. It also shows that even radical Bayesians must admit that systemic power is an integral component of (...) Bayesian reasoning. Finally, the paper puts the achieved results in perspective with van Fraassen’s famous criticism of IBE. (shrink)

Dans deux articles récents, Jaegwon Kim aborde le problème de l’explication de l’action d’une façon qui est centrée sur l’agent et fondée sur les raisons. Je soutiens que, bien qu’il prétende le contraire, la proposition de Kim ouvre la voie à une vision pluraliste de l’explication qui pourrait résoudre le problème de l’exclusion explicative et fournir un moyen permettant au physicalisme non réductionniste de se soustraire à l’argument de la survenance, aussi appelé argument de l’exclusion.

There is an explanatory constraint on practical reasons: practical reasons have to be the kinds of things that we can act for. Some philosophers, notably Bernard Williams, have argued that the explanatory constraint favours internalism about reasons: for an agent to have a reason to x, it is at least a necessary condition that she would, after ideal deliberation, be motivated to x. Internalism suggests that naturalism about reasons is more plausible for, in this (...) view, reasons are psychological states. However, reasons must not only be the kinds of things we can act for, at least some reasons must be good reasons, i.e. normative requirements. Derek Parfit argues that internalist, naturalist accounts cannot capture the normative aspect of reasons. He takes this to be a point in favour of his own externalist, non-naturalist account. I ask first whether Williams' account does fail to account for the normativity of reasons as Parfit argues, and second whether Parfit's externalist account can adequately meet the explanatory constraint. Although I claim that the answer to the first question is yes and the second no, the answer to both questions turns on the nature of practical rationality. My case stands if practical rationality is procedural, and falls if practical rationality is substantive. I argue, however, that the burden of proof is on those who, like Parfit, wish to defend a substantive account of practical rationality. S. Afr. J. Philos. Vol.24(2) 2005: 97-108. (shrink)

It is easy to accept that scientific reasoning cannot determine the characteristics of subjective experiences in cases like Broad’s archangel or Jackson’s Mary. The author questions why this seems to be evident and discusses the differences between these cases and ordinary scientific work, where future states of studied systems can be predicted in phenomenal terms. He concludes that important limitations of scientific reasoning are due to the inadequacy of human sensorial apparatus for representing physical reality. Such inadequacies were more evident (...) in Mary’s case, but are always present, and entail the existence of the explanatory gap. (shrink)

When an agent performs an action because she takes something as a reason to do so, does she take it as a normative reason for the action or as an explanatory reason? In Reasons Without Rationalism, Setiya criticizes the normative view and advances a version of the explanatory view. This paper advances a version of the normative view and shows that it is not subject to Setiya's criticisms. It also shows that Setiya's explanatory account is subject (...) to two fatal flaws, viz., that it raises questions about the occurrence of one motivational "because" within the scope of another which it cannot answer, and that it cannot accommodate the fact that, if an agent can φ for the reason that p, then she could take p as a reason to φ without φ-ing. (shrink)

In science and everyday life, we often infer that something is true because it would explain some set of facts better than any other hypothesis we can think of. But what if we have reason to believe that there is a better way to explain these facts that we just haven't thought of? Wouldn't that undermine our warrant for believing the best available explanation? Many philosophers have assumed that we can solve such underconsideration problems by stipulating that a hypothesis should (...) not only be 'the best' explanation available; rather, it should also be 'good enough'. Unfortunately, however, the only current suggestion for what it might mean to say that an explanation is 'good enough' is, well, not good enough. This paper aims to provide a better account of what is required for an explanatory hypothesis to be considered 'good enough'. In brief, the account holds that a `good enough' hypothesis is one that has gone through a process that I call explanatory consolidation, in which accumulating evidence and failed attempts to formulate better alternatives gradually make it more plausible that the explanation we currently have is better than any other that could be formulated. (shrink)

There is an ongoing controversy in philosophy about the connection between explanation and inference. According to Bayesians, explanatory considerations should be given weight in determining which inferences to make, if at all, only insofar as doing so is compatible with Strict Conditionalization. Explanationists, on the other hand, hold that explanatory considerations can be relevant to the question of how much confidence to invest in our hypotheses in ways which violate Strict Conditionalization. The controversy has focused on normative issues. (...) This paper investigates experimentally the descriptive question of whether judgments of the explanatory goodness of hypotheses do play a role when people revise their degrees of belief in those hypotheses upon the receipt of new evidence. We present the results of three experiments that together strongly support the predictive superiority of the explanationist position. (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)

Abductive reasoning assigns special status to the explanatory power of a hypothesis. But how do people make explanatory judgments? Our study clarifies this issue by asking: How does the explanatory power of a hypothesis cohere with other cognitive factors? How does probabilistic information affect explanatory judgments? In order to answer these questions, we conducted an experiment with 671 participants. Their task was to make judgments about a potentially explanatory hypothesis and its cognitive virtues. In the (...) responses, we isolated three constructs: Explanatory Value, Rational Acceptability, and Entailment. Explanatory judgments strongly cohered with judgments of causal relevance and with a sense of understanding. Furthermore, we found that Explanatory Value was sensitive to manipulations of statistical relevance relations between hypothesis and evidence, but not to explicit information about the prior probability of the hypothesis. These results indicate that probabilistic information about statistical relevance is a strong determinant of Explanatory Value. More generally, our study suggests that abductive and probabilistic reasoning are two distinct modes of inference. (shrink)

The coherence of independent reports provides a strong reason to believe that the reports are true. This plausible claim has come under attack from recent work in Bayesian epistemology. This work shows that, under certain probabilistic conditions, coherence cannot increase the probability of the target claim. These theorems are taken to demonstrate that epistemic coherentism is untenable. To date no one has investigated how these results bear on different conceptions of coherence. I investigate this situation using Thagard’s ECHO model of (...) explanatory coherence. Thagard’s ECHO model provides a natural representation of the evidential significance of multiple independent reports. (shrink)

Is epistemic inconsistency a mere symptom of having violated other requirements of rationality—notably, reasons-responsiveness requirements? Or is inconsistency irrational on its own? This question has important implications for the debate on the normativity of epistemic rationality. In this paper, I defend a new account of the explanatory role of the requirement of epistemic consistency. Roughly, I will argue that, in cases where an epistemically rational agent is permitted to believe P and also permitted to disbelieve P, the consistency (...) requirement plays a distinct explanatory role. I will also argue that such a type of permissiveness is a live possibility when it comes to rational epistemic standards. (shrink)

This book explores the Bayesian approach to the logic and epistemology of scientific reasoning. Section 1 introduces the probability calculus as an appealing generalization of classical logic for uncertain reasoning. Section 2 explores some of the vast terrain of Bayesian epistemology. Three epistemological postulates suggested by Thomas Bayes in his seminal work guide the exploration. This section discusses modern developments and defenses of these postulates as well as some important criticisms and complications that lie in wait for the Bayesian epistemologist. (...) Section 3 applies the formal tools and principles of the first two sections to a handful of topics in the epistemology of scientific reasoning: confirmation, explanatory reasoning, evidential diversity and robustness analysis, hypothesis competition, and Ockham's Razor. (shrink)