This article discusses how inference to the best explanation can be justified as a practical meta - argument. It is, firstly, justified as a practical argument insofar as accepting the best explanation as true can be shown to further a specific aim. And because this aim is a discursive one which proponents can rationally pursue in — and relative to — a complex controversy, namely maximising the robustness of one’s position, IBE can be conceived, secondly, as a meta - (...) argument. My analysis thus bears a certain analogy to Sellars ’ well - known justification of inductive reasoning ; it is based on recently developed theories of complex argumentation. (shrink)

How do we go about weighing evidence, testing hypotheses, and making inferences? According to the model of _Inference to the Best Explanation_, we work out what to infer from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain the evidence as a sign that the hypothesis is correct. In _Inference to the Best Explanation_, Peter Lipton gives this important and influential idea the development and assessment it deserves. The (...) second edition has been substantially enlarged and reworked, with a new chapter on the relationship between explanation and Bayesianism, and an extension and defence of the account of contrastive explanation. It also includes an expanded defence of the claims that our inferences really are guided by diverse explanatory considerations, and that this pattern of inference can take us towards the truth. This edition of _Inference to the Best Explanation_ has also been updated throughout and includes a new bibliography. (shrink)

In his seminal Inference to the Best Explanation, Peter Lipton adopted a causal view of explanation and a broadly Millian view of how causal knowledge is obtained. This made his account vulnerable to critics who charged that Inference to the Best Explanation is merely a dressed-up version of Mill’s methods, which in the critics’ view do the real inductive work. Lipton advanced two arguments to protect Inference to the Best Explanation against this line of criticism: the problem (...) of multiple differences and the problem of inferred differences. Lipton claimed that these two problems show Mill’s method of difference to be largely unworkable unless it is embedded in an explanationist framework. Here I consider both arguments as well as the best Millian defense against them. Since the existing Millian defense is only partially successful, I will develop a new and improved account. As an integral part of the argument, I show that my solutions to the problems of multiple and inferred differences offer new insight into Lipton’s main case study: Ignaz Semmelweis’s discovery of the cause of childbed fever. I conclude that the method of difference can overcome Lipton’s challenges outside an explanationist framework. (shrink)

Van Fraassen (1989) argues that Inference to the Best Explanation is incoherent in the sense that adopting it as a rule for belief change will make one susceptible to a dynamic Dutch book. The present paper argues against this. A strategy is described that allows us to infer to the best explanation free of charge.

In a situation in which several explanations compete, is the one that is better qua explanation also the one we should regard as the more likely to be true? Realists usually answer in the affirmative. They then go on to argue that since realism provides the best explanation for the success of science, realism can be inferred to. Nonrealists, on the other hand, answer the above question in the negative, thereby renouncing the inference to realism. In this paper I (...) separate the two issues. In the first section it is argued that a rationale can be provided for the inference to the best explanation; in the second, that this rationale cannot justify an inference to realism. The defence of the inference rests on the claim that our standards of explanatory power are subject to critical examination, which, in turn, should be informed by empirical considerations. By means of a comparison of the realist's explanation for the success of science with that of conventionalism and instrumentalism it is then shown that realism does not offer a superior explanation and should not, therefore, be inferred to. (shrink)

This article generalizes the explanationist account of inference to the best explanation. It draws a clear distinction between IBE and abduction and presents abduction as the first step of IBE. The second step amounts to the evaluation of explanatory power, which consist in the degree of explanatory virtues that a hypothesis exhibits. Moreover, even though coherence is the most often cited explanatory virtue, on pain of circularity, it should not be treated as one of the explanatory virtues. Rather, coherence (...) should be equated with explanatory power and considered to be derivable from the other explanatory virtues: unification, explanatory depth and simplicity. (shrink)

Bayesians have traditionally taken a dim view of the Inference to the Best Explanation, arguing that, if IBE is at variance with Bayes ' rule, then it runs afoul of the dynamic Dutch book argument. More recently, Bayes ' rule has been claimed to be superior on grounds of conduciveness to our epistemic goal. The present paper aims to show that neither of these arguments succeeds in undermining IBE.

This article considers the prospects of inference to the best explanation as a method of confirming causal claims vis-à-vis the medical evidence of mechanisms. I show that IBE is actually descriptive of how scientists reason when choosing among hypotheses, that it is amenable to the balance/weight distinction, a pivotal pair of concepts in the philosophy of evidence, and that it can do justice to interesting features of the interplay between mechanistic and population level assessments.

Inference to the Best Explanation is an unrivalled exposition of a theory of particular interest to students both of epistemology and the philosophy of science.

It has recently been argued that a non-Bayesian probabilistic version of inference to the best explanation (IBE*) has a number of advantages over Bayesian conditionalization (Douven [2013]; Douven and Wenmackers [2017]). We investigate how IBE* could be generalized to uncertain evidential situations and formulate a novel updating rule IBE**. We then inspect how it performs in comparison to its Bayesian counterpart, Jeffrey conditionalization (JC), in a number of simulations where two agents, each updating by IBE** and JC, respectively, try (...) to detect the bias of a coin while they are only partially certain what side the coin landed on. We show that IBE** more often prescribes high probability to the actual bias than JC. We also show that this happens considerably faster, that IBE** passes higher thresholds for high probability, and that it in general leads to more accurate probability distributions than JC. (shrink)

This article compares inference to the best explanation with Bayes’s rule in a social setting, specifically, in the context of a variant of the Hegselmann–Krause model in which agents not only update their belief states on the basis of evidence they receive directly from the world, but also take into account the belief states of their fellow agents. So far, the update rules mentioned have been studied only in an individualistic setting, and it is known that in such a (...) setting both have their strengths as well as their weaknesses. It is shown here that in a social setting, inference to the best explanation outperforms Bayes’s rule according to every desirable criterion. 1 What Is Inference to the Best Explanation?2 Judging the Rules—By Which Lights?3 From an Individualistic to a Social Perspective 3.1 The Hegselmann–Krause model 3.2 A probabilistic extension of the Hegselmann–Krause model 3.3 Simulations4 Results and Discussion5 Interpretation6 Conclusion. (shrink)

I respond to the bad lot argument in the context of biological systematics. The response relies on the historical nature of biological systematics and on the availability of pattern explanations. The basic assumption of common descent enables systematic methodology to naturally generate candidate explanatory hypotheses. However, systematists face a related challenge in the issue of character analysis. Character analysis is the central problem for contemporary systematics, yet the general problem of which it is a case—what counts as evidence?—has not been (...) adequately discussed by proponents of inference to the best explanation. Facing this problem is the price of adopting abductive methods. I sketch an account of how systematists approach the problem of evidence. (shrink)

Many epistemologists take Inference to the Best Explanation (IBE) to be “fundamental.” For instance, Lycan (1988, 128) writes that “all justified reasoning is fundamentally explanatory reasoning.” Conee and Feldman (2008, 97) concur: “fundamental epistemic principles are principles of best explanation.” Call them fundamentalists. They assert that nothing deeper could justify IBE, as is typically assumed of rules of deductive inference, such as modus ponens. However, logicians account for modus ponens with the valuation rule for the material conditional. By (...) contrast, fundamentalists account for IBE with an ill-defined set of relations that happen to furnish their favorite set of inductive inferences. To our eye, this seems a little too convenient—there is too much room for ad hoc, just-so stories about the “striking” correspondence between our explanatory and inductive practices. We will argue that the (explanatory) pluralism adopted by the leading theorists of the best explanation—philosophers of science—undermines fundamentalism. Section 1 clarifies fundamentalism’s key tenets. Section 2 presents pluralism’s challenge to fundamentalism. Section 3 considers a potential fundamentalist reply to this challenge. Sections 4 through 6 canvass the leading candidates for developing this fundamentalist reply, showing each to be unsatisfactory. (shrink)

An interesting consequence of the structuralist theory of truth approximation, as developed in my From Instrumentalism to Constructive Realism, henceforth ICR, concerns so-called ‘inference to the best explanation’. It will be argued that this popular rule among scientific realists can better be replaced by, various kinds of, ‘inference to the best theory’.

This chapter contains sections titled: What is the Theory of Enactive Perception? Noë's Evidence for Enactive Perception The Case against Enactive Perception: Paralysis Conclusion.

Defenders of Inference to the Best Explanation claim that explanatory factors should play an important role in empirical inference. They disagree, however, about how exactly to formulate this role. In particular, they disagree about whether to formulate IBE as an inference rule for full beliefs or for degrees of belief, as well as how a rule for degrees of belief should relate to Bayesianism. In this essay I advance a new argument against non-Bayesian versions of IBE. My (...) argument focuses on cases in which we are concerned with multiple levels of explanation of some phenomenon. I show that in many such cases, following IBE as an inference rule for full beliefs leads to deductively inconsistent beliefs, and following IBE as a non-Bayesian updating rule for degrees of belief leads to probabilistically incoherent degrees of belief. (shrink)

In pedagogical contexts and in everyday life, we often come to believe something because it would best explain the data. What is it about the explanatory endeavor that makes it essential to everyday learning and to scientific progress? There are at least two plausible answers. On one view, there is something special about having true explanations. This view is highly intuitive: it’s clear why true explanations might improve one’s epistemic position. However, there is another possibility—it could be that the process (...) of seeking, generating, or evaluating explanations itself puts one in a better epistemic position, even when the outcome of the process is not a true explanation. In other words, it could be that accurate explanations are beneficial, or it could be that high-quality explaining is beneficial, where there is something about the activity of looking for an explanation that improves our epistemic standing. The main goal of this paper is to tease apart these two possibilities, both theoretically and empirically, which we align with “Inference to the Best Explanation” and “Explaining for the Best Inference”, respectively. We also provide some initial support for EBI and identify promising directions for future research. (shrink)

The first edition of Peter Lipton's Inference to the Best Explanation, which appeared in 1991, is a modern classic in the philosophy of science. Yet in the second edition of the book, Lipton proves that even a classic can be improved. Not only does Lipton elaborate and expand on the themes covered in the first edition, but he also adds a new chapter on Bayesianism. In particular, he attempts a reconciliation between the Bayesian approach and that offered by (...) class='Hi'>Inference to the Best Explanation (IBE). (shrink)

This paper discusses the nature and the status of inference to the best explanation. We outline the foundational role given IBE by its defenders and the arguments of critics who deny it any place at all ; argue that, on the two main conceptions of explanation, IBE cannot be a foundational inference rule ; sketch an account of IBE that makes it contextual and dependent on substantive empirical assumptions, much as simplicity seems to be ; show how that (...) account avoids the critics ' complaints and leaves IBE an important role ; and sketch how our account can clarify debates over IBE in arguments for scientific realism. (shrink)

Harman and Kulkarni provide a rigorous and informative discussion of reliable reasoning, drawing philosophical conclusions from the elegant formal results of statistical learning theory. They have presented a strong case that statistical learning theory is highly relevant to issues in philosophy and psychology concerning inductive inferences. Although I agree with their general thrust, I want to take issue with some of the philosophical and psychological conclusions they reach. I will first discuss the general problem of assessing norms and propose a (...) metanormative decision procedure that can then be applied to the assessment of inductive methods. In particular, I will apply it to the assessment of the method of inference that Harman and Kulkarni call transduction. (shrink)

Niiniluoto has offered an incisive and comprehensive review of the recent debates about abduction. There is little on which I disagree with him. So, in this commentary, I shall try to cast some doubts to the attempts to render Inference to the Best Explanation within a Bayesian framework.

Inference to the best explanation—or, IBE—tells us to infer from the available evidence to the hypothesis which would, if correct, best explain that evidence. As Peter Lipton puts it, the core idea driving IBE is that explanatory considerations are a guide to inference. But what is the epistemic status of IBE, itself? One issue of contemporary interest is whether it is possible to provide a justification for IBE itself which is non- objectionably circular. We aim to carve out (...) some new space in this debate. In particular, we suggest that the matter of whether a given rule-circular argument is objectionably circular itself depends crucially on some subtle distinctions which have been made in the recent literature on perceptual warrant. By bringing these debates together, a principled reason emerges for why some kinds of rule-circular justifications for IBE are considerably less objectionable than others. (shrink)

This paper considers how we decide whether to believe what we are told. Inference to the Best Explanation, a popular general account of non-demonstrative reasoning, is applied to this task. The core idea of this application is that we believe what we are told when the truth of what we are told would figure in the best explanation of the fact that we were told it. We believe the fact uttered when it is part of the best explanation of (...) the fact of utterance. Having provided some articulation of this account of testimonial inference, the paper goes on to consider whether the account is informative and whether it is plausible. (shrink)

It has been claimed that kinetic energy is an objective physical quantity whilst at the same time maintaining that potential energy is not. However, by making use of the method of ‘inference to the best explanation’, it may be readily concluded that potential energy is indeed an objective physical quantity. This is done for an example drawn from the foundations of modern chemistry. In order to do so, the criteria of what counts as ‘most probable’ and ‘most reasonable’ are (...) defined and then employed for choosing the best explanation. (shrink)

In the form of inference known as inference to the best explanation there are various ways to characterise what is meant by the best explanation. This paper considers a number of such characterisations including several based on confirmation measures and several based on coherence measures. The goal is to find a measure which adequately captures what is meant by 'best' and which also yields the truth with a high degree of probability. Computer simulations are used to show that (...) the overlap coherence measure achieves this goal, enabling the true explanation to be identified almost as often as an approach which simply selects the most probable explanation. Further advantages to this approach are also considered in the case where there is uncertainty in the prior probability distribution. (shrink)

Inference to the Best Explanation is usually employed in the Scientific Realism debates. As far as particular scientific theories are concerned, its most ready usage seems to be that of a theory of confirmation. There are however more uses of IBE, namely as an epistemological theory of testimony and as a means of categorising and justifying the sources of evidence. In this paper, I will present, develop and exemplify IBE as a theory of the quality of evidence - taking (...) examples from medicine and showing that IBE can thereby provide the epistemological underpinning and justify the criteria of grading quality of mechanistic evidence that have been recently provided in the Clarke et al. paper on how evidence of medical mechanisms is to be construed alongside population studies. (shrink)

This paper examines the justification for the hypothesis of extended cognition. HEC claims that human cognitive processes can, and often do, extend outside our head to include objects in the environment. HEC has been justified by inference to the best explanation. Both advocates and critics of HEC claim that we can infer the truth value of HEC based on whether HEC makes a positive or negative explanatory contribution to cognitive science. I argue that IBE cannot play this epistemic role. (...) A serious rival to HEC exists with a differing truth value, and this invalidates IBEs for both the truth and the falsity of HEC. Explanatory value to cognitive science is not a guide to the truth value of HEC.Keywords: Extended mind; Extended cognition; Embedded cognition; Externalism; Inference to the best explanation; Functionalism. (shrink)

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)

The common role of research programs in science and religion is now widely accepted. The next step in the methodology debate is to specify more concretely the shared standards for adequate explanations. The article presents a detailed account of the method of inference to the best explanation and gives examples of how the method can structure the philosophical and theological interaction with science. The resulting approach dispenses with deductive and inductive proofs of religious propositions and limits itself to initially (...) plausible hypotheses that are to be assessed according to their explanatory power. Only when a domain of data and a particular explanatory task have been specified can any serious claim be made that religious theories are equal or superior to their naturalistic alternatives. (shrink)

ABSTRACT There is a new argument form within theoretical biology. This form takes as input competing explanatory models; it yields as output the conclusion that one of these models is more plausible than the others. The driving force for this argument form is an analysis showing that one model exhibits more parametric robustness than its competitors. This article examines these inferences to the more robust explanation, analysing them as variants of inference to the best explanation. The article defines parametric (...) robustness and distinguishes it from more familiar kinds of robustness. The article also argues that parametric robustness is an explanatory virtue not subsumed by more familiar explanatory virtues, and that the plausibility verdicts in the conclusions of inferences to the more robust explanations are best interpreted as guidance for research activity, rather than claims about likely truth. 1Introducing Inference to the More Robust Explanation 2Inference to the More Robust Explanation in the Study of Apoptosis 2.1Regulating apoptosis 2.2Competing models and evidential indecision 2.3Measuring robustness 2.4Robustness as a guide to plausibility 2.5Varieties of robustness 3Inference to the More Robust Explanation as Inference to the Best Explanation 3.1The structure of inference to the best explanation 3.2Parametric robustness as an explanatory virtue rather than an explanandum 3.3Relation of parametric robustness to other explanatory virtues 4Epistemological Significance of Inference to the More Robust Explanation 4.1Plausibility in practice 4.2Plausibility in principle 5Conclusion. (shrink)

This paper presents a new problem for the inference rule commonly known as Inference to the Best Explanation (IBE). The problem is that uncertainty about parts of one’s evidence may undermine the inferrability of a hypothesis that would provide the best explanation of that evidence, especially in cases where there is an alternative hypothesis that would provide a better explanation of only the more certain pieces of evidence. A potential solution to the problem is sketched, in which IBE (...) is generalized to handle uncertain evidence by invoking a notion of evidential robustness. (shrink)

Science depends on judgments of the bearing of evidence on theory. Scientists must judge whether an observation or the result of an experiment supports, disconfirms, or is simply irrelevant to a given hypothesis. Similarly, scientists may judge that, given all the available evidence, a hypothesis ought to be accepted as correct or nearly so, rejected as false, or neither. Occasionally, these evidential judgments can be make on deductive grounds. If an experimental result strictly contradicts a hypothesis, then the truth of (...) the evidence deductively entails the falsity of the hypothesis. In the great majority of cases, however, the connection between evidence and hypothesis is nondemonstrative or inductive. In particular, this is so whenever a general hypothesis is inferred to be correct on the basis of the available data, since the truth of the data will not deductively entail the truth of the hypothesis. It always remains possible that the hypothesis is false even though the data are correct. (shrink)

Inference is elementary and ubiquitous: Cognition always goes beyond the data. Thinking—including problem solving, decision making, judgement, planning, and argumentation—is here defined as the deliberate application and coordination of one's inferences to serve one's purposes. Reasoning, in turn, is epistemologically self-constrained thinking in which the application and coordination of inferences is guided by a metacognitive commitment to what are deemed to be justifiable inferential norms. The construction of rationality, in this view, involves increasing consciousness and control of logical and (...) other inferences. This metacognitive conception of rationality begins with logic rather than ending with it, and allows for developmental progress without positing a state of maturity. (shrink)

Christian apologists, like Willian Lane Craig and Stephen T. Davis, argue that belief in Jesus’ resurrection is reasonable because it provides the best explanation of the available evidence. In this article, I refute that thesis. To do so, I lay out how the logic of inference to the best explanation (IBE) operates, including what good explanations must be and do by definition, and then apply IBE to the issue at hand. Multiple explanations—including (what I will call) The Resurrection Hypothesis, (...) The Lie Hypothesis, The Coma Hypothesis, The Imposter Hypothesis, and The Legend Hypothesis—will be considered. While I will not attempt to rank them all from worst to best, what I will reveal is how and why The Legend Hypothesis is unquestionably the best explanation, and The Resurrection Hypothesis is undeniably the worst. Consequently, not only is Craig and Davis’ conclusion mistaken, but belief in the literal resurrection of Jesus is irrational. In presenting this argument, I do not take myself to be breaking new ground; Robert Cavin and Carlos Colombetti have already presented a Bayesian refutation of Craig and Davis’ arguments. But I do take myself to be presenting an argument that the average person (and philosopher) can follow. It is my goal for the average person (and philosopher) to be able to clearly understand how and why the hypothesis “God supernaturally raised Jesus from the dead” fails utterly as an explanation of the evidence that Christian apologist cite for Jesus’ resurrection. (shrink)

Some recent writers on practical reasoning have had it that reasoning about what to do differs in logical structure from theoretical reasoning. In particular, Anthony Kenny and G.E.M. Anscombe have argued that there are permissible inferences in practical reasoning which lack analogues in theoretical reasoning. Such discussions seem inevitably to draw their impetus from what Aristotle had to say on the topic, both in the Nicomachean Ethics and elsewhere.

In this article, I will provide a critical overview of the form of non-deductive reasoning commonly known as “Inference to the Best Explanation” (IBE). Roughly speaking, according to IBE, we ought to infer the hypothesis that provides the best explanation of our evidence. In section 2, I survey some contemporary formulations of IBE and highlight some of its putative applications. In section 3, I distinguish IBE from C.S. Peirce’s notion of abduction. After underlining some of the essential elements of (...) IBE, the rest of the entry is organized around an examination of various problems that IBE confronts, along with some extant attempts to address these problems. In section 4, I consider the question of when a fact requires an explanation, since presumably IBE applies only in cases where some explanation is called for. In section 5, I consider the difficult question of how we ought to understand IBE in light of the fact that among philosophers, there is significant disagreement about what constitutes an explanation. In section 6, I consider different strategies for justifying the truth-conduciveness of the explanatory virtues, e.g., simplicity, unification, scope, etc., criteria which play an indispensable role in any given application of IBE. In section 7, I survey some of the most recent literature on IBE, much of which consists of investigations of the status of IBE from the standpoint of the Bayesian philosophy of science. (shrink)

Inference to the best explanation (IBE) is a pattern of everyday and scientific reasoning, where a hypothesis is accepted if it gives a better explanation of the known evidence than any alternative hypothesis. This term was introduced by Gilbert Harman in 1965, and ever since IBE has been a central theme in the agenda of logic, artificial intelligence, and philosophy of science. However, a similar idea of a special kind of ampliative reasoning (besides deduction and induction) had been advocated (...) by Charles S. Peirce already a century earlier: “hypothetical reasoning” proceeds backward from effects to causes, or “abduction” leads from surprising facts to explanatory theories. The key issues in the explication of IBE concern the definition of “the best explanation” and the possibility of analyzing the nature of explanatory reasoning by the Bayesian probabilistic approach or by the truthlikeness framework. -/- . (shrink)

How can new drug lead suggestions beinferred from neurophysiological models? This paperaddresses this question based on a case study ofresearch into Parkinson''s disease at the GroningenUniversity Department of Pharmacy. It is argued thatneurophysiological box-and-arrow models can beunderstood as qualitative differential equationmodels. An inference task is defined to helpunderstand and possibly aid the discovery andexplanation of new drug lead suggestions.

Conspiracy theories are typically thought to be examples of irrational beliefs, and thus unlikely to be warranted. However, recent work in Philosophy has challenged the claim that belief in conspiracy theories is irrational, showing that in a range of cases, belief in conspiracy theories is warranted. However, it is still often said that conspiracy theories are unlikely relative to non-conspiratorial explanations which account for the same phenomena. However, such arguments turn out to rest upon how we define what gets counted (...) both as a ‘conspiracy’ and a ‘conspiracy theory’, and such arguments rest upon shaky assumptions. It turns out that it is not clear that conspiracy theories are prima facie unlikely, and so the claim that such theories do not typically appear in our accounts of the best explanations for particular kinds of events needs to be reevaluated. (shrink)

In his work on the epistemology of testimony, Peter Lipton developed an account of testimonial inference that aimed at descriptive adequacy as well as justificatory sophistication. According to ‘testimonial inference to the best explanation’, we accept what a speaker tells us because the truth of her claim figures in the best explanation of the fact that she made it. In this paper, I argue for a modification of this picture. In particular, I argue that IBE plays a dual (...) role in the management and justification of testimony. On the one hand, the coherence and success of our testimony-based projects provides general abductive support for a default stance of testimonial acceptance; on the other hand, we are justified in rejecting specific testimonial claims whenever the best explanation of the instances of testimony we encounter entails, or makes probable, the falsity or unreliability of the testimony in question.Keywords: Testimony; Inference to the best explanation; Abduction; Epistemic justification. (shrink)

Peter Lipton has attempted to flesh out a model of Inference to the Best Explanation (IBE) by clarifying explanation in terms of a causal model. But Lipton's account of explanation makes an adequate explanation depend on a principle which is virtually identical to Mill's Method of Difference. This has the result of collapsing IBE on Lipton's account of it into causal inference as conceived by the Causal-Inference model of induction. According to this model, many of our inductions (...) are inferences from effects to their probable causes, and Mill's Methods are canons to guide such inferences. Thus, Lipton's account of IBE fails to represent an advance over the already familiar Causal-Inference Model of induction. (shrink)

The book is a defence of scientific realism. Its primary aim is to argue that it is possible to establish scientific realism without Inference to the Best Explanation. The idea that plays the central role in the book is an "Eddington-inference". Arthur Eddington once considered a hypothetical ichthyologist who concluded from the fact that his net contained no fish smaller than the holes in his net that there were in the sea no fish smaller than the holes in (...) his net. Although Eddington himself defended the inference, the author of the present volume argues on probabilistic grounds that it is likely such an inference is flawed. He generalises the argument to develop a probabilistic justification for scientific realist claims about the existence of unobservable entities. (shrink)

Inference to the Best Explanation has become the subject of a livelydebate in the philosophy of science. Scientific realists maintain, while scientificantirealists deny, that it is a compelling rule of inference. It seems that anyattempt to settle this debate empirically must beg the question against theantirealist. The present paper argues that this impression is misleading. A methodis described that, by combining Glymour's theory of bootstrapping and Hacking'sarguments from microscopy, allows us to test IBE without begging any antirealistissues.

Seungbae Park argues that Bas van Fraassen’s rejection of inference to the best explanation (IBE) is problematic for his contextual theory of explanation because van Fraassen uses IBE to support the contextual theory. This paper provides a defense of van Fraassen’s views from Park’s objections. I point out three weaknesses of Park’s objection against van Fraassen. First, van Fraassen may be perfectly content to accept the implications that Park claims to follow from his views. Second, even if van Fraassen (...) rejects IBE he may still endorse particular arguments that instantiate IBE. Third, van Fraassen does not, in fact, use IBE to support his contextual theory. (shrink)