In Logik der Forschung (1934) and later works, Karl Popper proposed a set of methodological rules for scientists. Among these were requirements that theories should evolve in the direction of increasing content, and that new theories should only be accepted if some of their novel predictions are experimentally confirmed. There are currently two, viable theories of cosmology: the standard cosmological model, and a theory due to Mordehai Milgrom called MOND. Both theories can point to successes and failures, but only MOND (...) has repeatedly made novel predictions that were subsequently found to be correct. Standard-model cosmologists, by contrast, have almost always responded to new observations in a post-hoc manner, adjusting or augmenting their theory as needed to obtain correspondence with the facts. I argue that these methodological differences render a comparison of the two theories in terms of their ‘truthlikeness’ or ‘verisimilitude’ essentially impossible since the two groups of scientists achieve correspondence with the facts in fundamentally different ways, and I suggest that a better guide to the theories’ progress toward the truth might be the methodologies themselves. (shrink)

I develop a probabilistic account of coherence, and argue that at least in certain respects it is preferable to (at least some of) the main extant probabilistic accounts of coherence: (i) Igor Douven and Wouter Meijs’s account, (ii) Branden Fitelson’s account, (iii) Erik Olsson’s account, and (iv) Tomoji Shogenji’s account. Further, I relate the account to an important, but little discussed, problem for standard varieties of coherentism, viz., the “Problem of Justified Inconsistent Beliefs.”.

In this paper I adduce a new argument in support of the claim that IBE is an autonomous form of inference, based on a familiar, yet surprisingly, under-discussed, problem for Hume’s theory of induction. I then use some insights thereby gleaned to argue for the claim that induction is really IBE, and draw some normative conclusions.

The background of this paper (section 1) consists in a new account to foundation‐theoretic epistemology characterized by two features: (i) All beliefs are to be justified by deductive, inductive or abductive inferences from a minimalistic class of unproblematic (introspective or analytic) basic beliefs. (ii) Higher‐order justifications for these inferences are given by means of the novel method of optimality justifications. Optimality justifications are a new tool for epistemology (section 2). An optimality justification does not attempt todemonstratethat a cognitive method is (...) reliable (which is impossible), but pursues the more modest goal of demonstrating that the method isoptimalamong all accessible alternative methods for the given epistemic goal. The reasoning from the established optimality of a method to the acceptability of a particular belief generated by the method is accomplished by so‐called optimality principles. In sections 3–5, the method of optimality justifications is carried out in detail for three fundamental problems: justifying induction, logic, and theory‐generating abduction. (shrink)

In this paper, the contributions to the account of meta-induction (Schurz 2019) collected in this volume are critically discussed and thereby, new insights are developed. How broad and expandable the program of meta-induction is can be learned from Ortner’s contribution. New insights about the transition from the a priori justification of meta-induction to the a posteriori justification of object-induction emerge from the reflection of Shogenji’s paper. How meta-induction may be applied also to religious prophecies and that their meta-inductive justification does (...) not fail for a priori reasons but because of missing evidence for predictive success is learned from the discussion of Pitts’ contribution. That meta-induction does not rely on a particular prior distribution, while the no free lunch theorem depends implicitly on a uniform prior, is the major conclusion drawn from the discussion of Wolpert’s article. How the problem of induction is treated in different versions of the Bayesian account is learned from the discussion of Willliamson’s paper. That meta-induction can also be employed for abduction, and that abductive theory-revision can offer meta-inductive aggregation methods is a new insight emerging from the reflection of Aliseda’s contribution. (shrink)

This essay introduces two leading Finnish philosophers of the twentieth century, Eino Kaila and Georg Henrik von Wright, who not only established analytic philosophy in Finland but also made original contributions to the development of pragmatism. The pragmatist dimensions of Kaila’s thought were clearly influenced by the classical American pragmatists, primarily William James, whose writings Kaila read and commented on already at an early stage of his career in the 1910s. Kaila then continued to develop a quasi-pragmatist idea of “practical (...) testability” during his logical empiricist period in the 1930s and 1940s. Unlike Kaila, von Wright was never directly inspired by James or any other classical pragmatists, although he did refer to Peirce and James as informal precursors of logical empiricism in the 1940s. His highly original theories of human action and causation, mostly developed in the 1970s, contain interesting pragmatist aspects, however. Both Kaila and von Wright, moreover, shared a life-long engagement with an issue that also troubled all the classical pragmatists: a reconciliation of a “humanist” philosophy with a thoroughgoing appreciation of the natural sciences. Thus, they both developed non-reductive versions of naturalism (or naturalist versions of pragmatist humanism) that, in their emphasis on the disunity of science, were not terribly far from the positions of classical pragmatists like James and Dewey. (shrink)

The background target of the research going into the present article is to forge an intellectual alliance between, on the one hand, active inference and the free-energy principle (FEP), and on the other, Charles S. Peirce’s theory of semiotics and pragmatism. In the present paper, the focus is on the allegiance between the nomenclatures of active and abductive inferences as the proper place to begin reaching at that wider target. The paper outlines the key conceptual elements involved in a naturalistic (...) rendering of Peirce’s late semiotic and logical notion of abductive reasoning. The target is a cognitive-biological model of abduction which preserves the functional integrity of an organism and fulfils the existential imperative for living beings’ evidence of existence. Such a model is an adaptation of Peirce’s late logical schema of abduction proposed in his largely unpublished works during the early 20th century. The proposed model is argued to be a feasible sketch also of recent breakthroughs in computational (sensu Bayesian) cognitive science. (shrink)

Abductive reasoning involves finding the missing premise of an “unsaturated” deductive inference, thereby selecting a possible _explanans_ for a conclusion based on a set of previously accepted premises. In this paper, we explore abductive reasoning from a structural proof-theory perspective. We present a hybrid sequent calculus for classical propositional logic that uses sequents and antisequents to define a procedure for identifying the set of analytic hypotheses that a rational agent would be expected to select as _explanans_ when presented with an (...) abductive problem. Specifically, we show that this set may not include the deductively minimal hypothesis due to the presence of redundant information. We also establish that the set of all analytic hypotheses exhausts all possible solutions to the given problem. Finally, we propose a deductive criterion for differentiating between the best _explanans_ candidates and other hypotheses. (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)

Scientific realists use the “no miracle argument” to show that the empirical and pragmatic success of science is an indicator of the ability of scientific theories to give true or truthlike representations of unobservable reality. While antirealists define scientific progress in terms of empirical success or practical problem-solving, realists characterize progress by using some truth-related criteria. This paper defends the definition of scientific progress as increasing truthlikeness or verisimilitude. Antirealists have tried to rebut realism with the “pessimistic metainduction”, but critical (...) realists turn this argument into an optimistic view about progressive science. (shrink)

In the general problem of verisimilitude, we try to define the distance of a statement from a target, which is an informative truth about some domain of investigation. For example, the target can be a state description, a structure description, or a constituent of a first-order language. In the problem of legisimilitude, the target is a deterministic or universal law, which can be expressed by a nomic constituent or a quantitative function involving the operators of physical necessity and possibility. The (...) special case of legisimilitude, where the target is a probabilistic law, has been discussed by Roger Rosenkrantz and Ilkka Niiniluoto. Their basic proposal is to measure the distance between two probabilistic laws by the Kullback–Leibler notion of divergence, which is a semimetric on the space of probability measures. This idea can be applied to probabilistic laws of coexistence and laws of succession, and the examples may involve discrete or continuous state spaces. In this paper, these earlier studies are elaborated in four directions. First, even though deterministic laws are limiting cases of probabilistic laws, the target-sensitivity of truthlikeness measures implies that the legisimilitude of probabilistic laws is not easily reducible to the deterministic case. Secondly, the Jensen-Shannon divergence is applied to mixed probabilistic laws which entail some universal laws. Thirdly, a new class of distance measures between probability distributions is proposed, so that their horizontal differences are taken into account in addition to vertical ones. Fourthly, a solution is given for the epistemic problem of estimating degrees of probabilistic legisimilitude on the basis of empirical evidence. (shrink)

After Karl Popper’s original work, several approaches were developed to provide a sound explication of the notion of verisimilitude. With few exceptions, these contributions have assumed that the truth to be approximated is deterministic. This collection of ten papers addresses the more general problem of approaching probabilistic truths. They include attempts to find appropriate measures for the closeness to probabilistic truth and to evaluate claims about such distances on the basis of empirical evidence. The papers employ multiple analytical approaches, and (...) connect the research to related issues in the philosophy of science. (shrink)

In this paper, I argue that the ultimate argument for Scientific Realism, also known as the No-Miracles Argument (NMA), ultimately fails as an abductive defence of Epistemic Scientific Realism (ESR), where (ESR) is the thesis that successful theories of mature sciences are approximately true. The NMA is supposed to be an Inference to the Best Explanation (IBE) that purports to explain the success of science. However, the explanation offered as the best explanation for success, namely (ESR), fails to yield independently (...) testable predictions that alternative explanations for success do not yield. If this is correct, then there seems to be no good reason to prefer (ESR) over alternative explanations for success. (shrink)

I discuss the relevance of the current predicament in cosmology to the debate over scientific realism. I argue that the existence of two, empirically successful but ontologically inconsistent cosmological theories presents difficulties for the realist position.

Truthlikeness is a property of a theory or a proposition that represents its closeness to the truth. We start by summarizing Niiniluoto’s proposal of truthlikeness for deterministic laws, which defines truthlikeness as a function of accuracy, and García-Lapeña’s expanded version, which defines truthlikeness for DL as a function of two factors, accuracy and nomicity. Then, we move to develop an appropriate definition of truthlikeness for probabilistic laws based on Niiniluoto’s suggestion to use the Kullback–Leibler divergence to define the distance between (...) a probability law X\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$X$$\end{document} and the true probability law T\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$T$$\end{document}. We argue that the Kullback–Leibler divergence seems to be the best of the available probability distances to measure accuracy between PL. However, as in the case of DL, we argue that accuracy represents a necessary but not sufficient condition, as two PL may be equally accurate and still one may imply more true or truthlike consequences, behaviours or true facts about the system than the other. The final proposal defines truthlikeness for PL as a function of two factors, p-accuracy and p-nomicity, in intimate connexion with García-Lapeña’s proposal for DL. (shrink)

Reverse inference is a crucial inferential strategy used in cognitive neuroscience to derive conclusions about the engagement of cognitive processes from patterns of brain activation. While widely employed in experimental studies, it is now viewed with increasing scepticism within the neuroscience community. One problem with reverse inference is that it is logically invalid, being an instance of abduction in Peirce’s sense. In this paper, we offer the first systematic analysis of reverse inference as a form of abductive reasoning and highlight (...) some relevant implications for the current debate. We start by formalising an important distinction that has been entirely neglected in the literature, namely the distinction between weak and strong reverse inference. Then, we rely on case studies from recent neuroscientific research to systematically discuss the role and limits of both strong and weak reverse inference; in particular, we offer the first exploration of weak reverse inference as a discovery strategy within cognitive neuroscience. (shrink)

Two powerful arguments have famously dominated the realism debate in philosophy of science: The No Miracles Argument (NMA) and the Pessimistic Meta-Induction (PMI). A standard response to the PMI is selective scientific realism (SSR), wherein only the working posits of a theory are considered worthy of doxastic commitment. Building on the recent debate over the NMA and the connections between the NMA and the PMI, I here consider a stronger inductive argument that poses a direct challenge for SSR: Because it (...) is sometimes exactly the working posits which contradict each other, i.e., that which is directly responsible for empirical success, SSR cannot deliver a general explanation of scientific success. (shrink)

This paper aims at elucidating the connection between explanatory considerations and epistemic justification stipulated by explanationism which take epistemic justification to be definable in terms of best explanations. By relying on the notion of truthlikeness, this paper argues that it is rational for a subject to expect the best explanation she has for her evidence to be more truthlike than any of the other potential explanations available to her by virtue of containing a class of propositions that, given her evidence, (...) she is justified in believing. Based on this elucidation of the connection between explanatory considerations and epistemic justification, an explanationist account of the evidential support relation is then offered. (shrink)

A methodology of science must satisfy two requirements: (i) It must be ampliative: the theories which it generates must make statements that go far beyond any data or observations that may have motivated those theories in the first place. (ii) It must be epistemically probative: it must somehow provide a warrant for believing that the theories so produced are correct, or at least partially correct, even if they can never be fully confirmed. These two requirements pull in opposite directions, and (...) attempts to specify the “scientific method” often focus on one to the exclusion of the other. On a few points there now exists something approaching a consensus. (i) Scientific hypotheses — including, particularly, statements about unobserved or unobservable entities or mechanisms — remain conjectural, no matter how frequently predictions based on those hypotheses are found to coincide with data. (ii) A good (best?) indicator of a theory’s verisimilitude is its ability to successfully predict phenomena which it was not specifically designed to predict. I discuss these ideas with particular reference to cosmological theories. (shrink)

Aliseda’s Abductive Reasoning is focused on the logical problem of abduction. My paper, in contrast, deals with the epistemic problems raised by this sort of inference. I analyze the relation between abduction and inference to the best explanation (IBE). Firstly a heuristic and a normative interpretation of IBE are distinguished. The epistemic problem is particularly pressing for the latter interpretation, since it is devoid of content without specific epistemic criteria for separating acceptable explanations from those which are not. Then I (...) discuss two different normative interpretations of IBE. I. Niiniliuoto favours a “probabilistic-confirmational” translation of explanatory merit while S. Psillos thinks that the insight of IBE is lost in a pure probabilistic format. My conclusion is that Aliseda’s theory of abduction fits better with a heuristic account of IBE. (shrink)

I begin by making some distinctions between kinds of response to a skeptical claim, the purpose of which is to explain what I mean by a "dissolution" of the problem of induction, and to focus on one of the ways it can be implemented. I then argue that previous attempts to dissolve the problem in this way fail, present mine, and defend it. Finally, I show that the dissolution of the problem doesn't improve our normative situation and may even worsen (...) it. (shrink)

In this talk I present the main results from Anta (2021), namely, that the theoretical division between Boltzmannian and Gibbsian statistical mechanics should be understood as a separation in the epistemic capabilities of this physical discipline. In particular, while from the Boltzmannian framework one can generate powerful explanations of thermal processes by appealing to their microdynamics, from the Gibbsian framework one can predict observable values in a computationally effective way. Finally, I argue that this statistical mechanical schism contradicts the Hempelian (...) (1958) thesis that the predictive power of a scientific theory is directly proportional to its explanatory potential, and vice versa. (shrink)

Bayesianism and Inference to the best explanation are two different models of inference. Recently there has been some debate about the possibility of “bayesianizing” IBE. Firstly I explore several alternatives to include explanatory considerations in Bayes’s Theorem. Then I distinguish two different interpretations of prior probabilities: “IBE-Bayesianism” and “frequentist-Bayesianism”. After detailing the content of the latter, I propose a rule for assessing the priors. I also argue that Freq-Bay: endorses a role for explanatory value in the assessment of scientific hypotheses; (...) avoids a purely subjectivist reading of prior probabilities; and fits better than IBE-Bayesianism with two basic facts about science, i.e., the prominent role played by empirical testing and the existence of many scientific theories in the past that failed to fulfil their promises and were subsequently abandoned. (shrink)