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Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have adopted a realist attitude towards the results of Bayesian cognitive science. In this article, we argue that this realist attitude is unwarranted. The Bayesian research programme in cognitive science does not possess special epistemic virtues over alternative approaches for explaining mental phenomena involving uncertainty. In particular, the Bayesian approach is not simpler, more unifying, or more rational than alternatives. It is also contentious that the Bayesian approach is overall better supported by the empirical evidence. So, to develop philosophical theories of mind on the basis of a realist interpretation of results from Bayesian cognitive science is unwarranted. Naturalistic philosophers of mind should instead adopt an anti-realist attitude towards these results and remain agnostic as to whether Bayesian models are true. For continuing on with an exclusive focus and praise of Bayes within debates about the predictive processing theory will impede progress in philosophical understanding of scientific practice in computational cognitive science as well as of the architecture of the mind. more...

According to orthodoxy, there are two basic moods of supposition: indicative and subjunctive. The most popular formalizations of the corresponding norms of suppositional judgement are given by Bayesian conditionalization and Lewisian imaging, respectively. It is well known that Bayesian conditionalization can be generalized (via Jeffrey conditionalization) to provide a model for the norms of partial indicative supposition. This raises the question of whether imaging can likewise be generalized to model the norms of ‘partial subjunctive supposition’. The present article casts doubt on whether the most natural generalizations of imaging are able to provide a plausible account of the norms of partial subjunctive supposition . more...

Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection fit into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the field. Moreover, we argue that philosophers contribute to computational modeling not only by building their own models, but also by thinking about the various applications of the method in philosophy and the sciences. In this context, we note that models in philosophy are usually simple, while models in the sciences are often more complex and empirically grounded. Bridging certain methodological gaps that arise from this discrepancy may prove to be challenging and fruitful for the further development of computational modeling in philosophy and beyond. more...

Whether y obtains under the counterfactual supposition that x is thought to depend on whether y obtains in the most similar world(s) in which x obtains. Graphical causal models have proved useful in developing a principled notion of similarity between worlds, but this notion is limited insofar as it does not apply to counterfactual suppositions about causal structure. Here, we explore the possibility of filling this lacuna by introducing a notion of similarity between causal graphs. Since there are multiple principled senses in which graphs can be similar, we introduce multiple similarity metrics and multiple ways to prioritize these metrics. more...

We present a Bayesian analysis of the epistemology of analogue experiments with particular reference to Hawking radiation. First, we prove that such experiments can be confirmatory in Bayesian terms based upon appeal to 'universality arguments'. Second, we provide a formal model for the scaling behaviour of the confirmation measure for multiple distinct realisations of the analogue system and isolate a generic saturation feature. Finally, we demonstrate that different potential analogue realisations could provide different levels of confirmation. Our results provide a basis both to formalise the epistemic value of analogue experiments that have been conducted and to advise scientists as to the respective epistemic value of future analogue experiments., 25 pages, 5 figures more...

In this article, we address a major outstanding question of probabilistic Bayesian epistemology: how should a rational Bayesian agent update their beliefs upon learning an indicative conditional? A number of authors have recently contended that this question is fundamentally underdetermined by Bayesian norms, and hence that there is no single update procedure that rational agents are obliged to follow upon learning an indicative conditional. Here we resist this trend and argue that a core set of widely accepted Bayesian norms is sufficient to identify a normatively privileged updating procedure for this kind of learning. Along the way, we justify a privileged formalization of the notion of ‘epistemic conservativity’, offer a new analysis of the Judy Benjamin problem, and emphasize the distinction between interpreting the content of new evidence and updating one’s beliefs on the basis of that content. more...

Industrial plants suffer from a high degree of complexity and incompatibility in their communication infrastructure, caused by a wild mix of proprietary technologies. This prevents transformation towards Industry 4.0 and the Industrial Internet of Things. Open Platform Communications Unified Architecture (OPC UA) is a standardized protocol that addresses these problems with uniform and semantic communication across all levels of the hierarchy. However, its adoption in embedded field devices, such as sensors and actors, is still lacking due to prohibitive memory and power requirements of software implementations. We have developed a dedicated hardware engine that offloads processing of the OPC UA protocol and enables realization of compact and low-power field devices with OPC UA support. As part of a proof-of-concept embedded system we have implemented this engine in a 22 nm FDSOI technology. We measured performance, power consumption, and memory footprint of our test chip and compared it with a software implementation based on open62541 and a Raspberry Pi 2B. Our OPC UA hardware engine is 50 times more energy efficient and only requires 36 KiB of memory. The complete chip consumes only 24 mW under full load, making it suitable for low-power embedded applications., 5 pages, 6 figures, 2 tables more...

The philosophy of science community mourns the loss of Margaret Catherine Morrison, who passed away on January 9, 2021, after a long battle with cancer. Margie, as she was known to all who knew her, was highly regarded for her influential contributions to the philosophy of science, particularly her studies of the role of models and simulations in the natural and social sciences. These contributions made her a world-leading philosopher of science, instrumental in shifting philosophers' attention from the structure of scientific theories to the practice of science. Her sophisticated studies of the function of models in scientific practice drew on detailed knowledge of the theories and experiments of physics as well as the history of physics. In emphasizing the autonomy of scientific models and their interventional character, her insights had some affinity with Cartwright's and Hacking’s views on phenomenological laws, entity realism, the instrumentalist interpretation of scientific theories, and the disunity of science. But Morrison’s approach was distinguished by the conviction that the existence of unobservable entities cannot be defended independently of the theories that support their evidence, and that scientific practice cannot be adequately understood without examining the reasons for theory unification., Journal for general philosophy of science;Vol. 52. 2021, pp 25–33 more...

We argue that social deliberation may increase an agent’s confidence and credence under certain circumstances. An agent considers a proposition H and assigns a probability to it. However, she is not fully confident that she herself is reliable in this assignment. She then endorses H during deliberation with another person, expecting him to raise serious objections. To her surprise, however, the other person does not raise any objections to H. How should her attitudes toward H change? It seems plausible that she should (i) increase the credence she assigns to H and, at the same time, (ii) increase the reliability she assigns to herself concerning H (i.e. her confidence). A Bayesian model helps us to investigate under what conditions, if any, this is rational. more...

The way in which philosophers have thought about the scientific method and the nature of good scientific reasoning over the last few centuries has been consistently and heavily influenced by the examples set by physics. The astounding achievements of 19th and 20th century physics demonstrated that physicists had successfully identified methodologies and reasoning patterns that were uniquely well suited to discovering fundamental truths about the natural world. Inspired by this success, generations of philosophers set themselves the goal of taxonomising, codifying, formalising and evaluating these reasoning patterns. Many will concede that this has been a tremendously fruitful exercise that has served both to illuminate characteristic methodological and epistemological features of the physical sciences, and to inform the way that philosophers think about the epistemic ideals served by science more generally. published more...

Conditionals and conditional reasoning have been a long-standing focus of research across a number of disciplines, ranging from psychology through linguistics to philosophy. But almost no work has concerned itself with the question of how hearing or reading a conditional changes our beliefs. Given that we acquire much-perhaps most-of what we believe through the testimony of others, the simple matter of acquiring conditionals via others' assertion of a conditional seems integral to any full understanding of the conditional and conditional reasoning. In this paper we detail a number of basic intuitions about how beliefs might change in response to a conditional being uttered, and show how these are backed by behavioral data. In the remainder of the paper, we then show how these deceptively simple phenomena pose a fundamental challenge to present theoretical accounts of the conditional and conditional reasoning - a challenge which no account presently fully meets. more...

Deliberation is a standard procedure to make decisions in not too large groups. It has the advantage that the group members can learn from each other and that, at the end, often a consensus emerges that everybody endorses. But a deliberation procedure also has a number of disadvantages. E.g., what consensus is reached usually depends on the order in which the different group members speak. More specifically, the group member who speaks first often has an unproportionally high impact on the final decision: She anchors the deliberation process. While the anchoring effect undoubtably appears in real deliberating groups, we ask whether it also appears in groups whose members are truth-seeking and rational in the sense that they take the information provided by their fellow group members properly into account by updating their beliefs according to plausible rules. To answer this question and to make some progress towards explaining the anchoring effect, a formal model is constructed and analyzed. Using this model, we study the anchoring effect in homogenous groups (i.e. groups whose members consider each other as equally reliable), for which we provide analytical results, and in inhomogeneous groups, for which we provide simulation results. more...

According to the Bayesian paradigm in the psychology of reasoning, the norms by which everyday human cognition is best evaluated are probabilistic rather than logical in character. Recently, the Bayesian paradigm has been applied to the domain of argumentation, in which the fundamental norms are traditionally assumed to be logical. Here, we present a major generalization of extant Bayesian approaches to argumentation that (a) utilizes a new class of Bayesian learning methods that are better suited to modeling dynamic and conditional inferences than standard Bayesian conditionalization, (b) is able to characterize the special value of logically valid argument schemes in uncertain reasoning contexts, (c) greatly extends the range of inferences and argumentative phenomena that can be adequately described in a Bayesian framework, and (d) undermines some influential theoretical motivations for dual function models of human cognition. We conclude that the probabilistic norms given by the Bayesian approach to rationality are not necessarily at odds with the norms given by classical logic. Rather, the Bayesian theory of argumentation can be seen as justifying and enriching the argumentative norms of classical logic. (PsycINFO Database Record (c) 2018 APA, all rights reserved). more...

Intertheoretic relations are an important topic in the philosophy of science. However, since their classical discussion by Ernest Nagel, such relations have mostly been restricted to relations between pairs of theories in the natural sciences. This paper presents a case study of a new type of intertheoretic relation that is inspired by Montague’s analysis of the linguistic syntax-semantics relation. The paper develops a simple model of this relation. To motivate the adoption of our new model, we show that this model extends the scope of application of the Nagelian (or related) models and that it shares the epistemological advantages of the Nagelian model. The latter is achieved in a Bayesian framework. more...

In the long run, the development of artificial intelligence (AI) is likely to be one of the biggest technological revolutions in human history. Even in the short run it will present tremendous challenges as well as tremendous opportunities. The more we do now to think through these complex challenges and opportunities, the better the prospects for the kind of outcomes we all hope for, for ourselves, our children, and our planet. more...

According to an argument by Colin Howson, the no-miracles argument (NMA) is contingent on committing the base-rate fallacy and is therefore bound to fail. We demonstrate that Howson’s argument only applies to one of two versions of the NMA. The other version, which resembles the form in which the argument was initially presented by Putnam and Boyd, remains unaffected by his line of reasoning. We provide a formal reconstruction of that version of the NMA and show that it is valid. Finally, we demonstrate that the use of subjective priors is consistent with the realist implication of the NMA and show that a core worry with respect to the suggested form of the NMA can be dispelled. more...

Convincing scientific theories are often hard to find, especially when empirical evidence is scarce (e.g., in particle physics). Once scientists have found a theory, they often believe that there are not many distinct alternatives to it. Is this belief justified? We model how the failure to find a feasible alternative can increase the degree of belief in a scientific theory—in other words, we establish the validity of the No Alternatives Argument and the possibility of non-empirical theory confirmation from a Bayesian point of view. Then we evaluate scope and limits of this argument (e.g., by calculating the degree of confirmation it provides) and relate it to other argument forms such as Inference to the Best Explanation (IBE) or “There is No Alternative” (TINA). more...

Confirmation of scientific theories by empirical evidence is an important element of scientific reasoning and a central topic in philosophy of science. Bayesian Confirmation Theory—the analysis of confirmation in terms of degree of belief—is the most popular model of inductive reasoning. It comes in two varieties: confirmation as firmness (of belief), and confirmation as increase in firmness. We show why increase in firmness is a particularly fruitful explication of degree of confirmation, and how it resolves longstanding paradoxes of inductive inference (e.g., the paradox of the ravens, the tacking paradoxes and the grue paradox). Finally, we give an axiomatic characterization of various confirmation measures and we discuss the question of whether there is a single adequate measure of confirmation or whether a pluralist position is more promising more...

Scientific theories are hard to find, and once scientists have found a theory H, they often believe that there are not many distinct alternatives to H. But is this belief justified? What should scientists believe about the number of alternatives to H, and how should they change these beliefs in the light of new evidence? These are some of the questions that we will address in this paper. We also ask under which conditions failure to find an alternative to H confirms the theory in question. This kind of reasoning (which we call the No Alternatives Argument) is frequently used in science and therefore deserves a careful philosophical analysis. more...

Southern anthracnose caused by Colletotrichum trifolii can lead to severe losses of red clover plants. To ensure the cultivation of red clover in the event of this disease spreading, cultivars listed in Germany were evaluated in a resistance test in the greenhouse concerning their susceptibility to the pathogen. Plant survival varied from 32.7 to 90.2 % seven weeks after inoculation. Varieties with a high level of resistance were identified. Recurrent selection based on greenhouse screening was ascertained to be a potential method for improving the resistance level of existing populations. For this trait, selection success was between 1.9 and 14.0 % per year. The heritability of resistance to southern anthracnose seems to be moderate with h2 between 0.21 and 0.37 for the test populations. more...

In this work, we present a mathematical model for the emergence of descriptive norms, where the individual decision problem is formalized with the standard Bayesian belief revision machinery. Previous work on the emergence of descriptive norms has relied on heuristic modeling. In this paper we show that with a Bayesian model we can provide a more general picture of the emergence of norms, which helps to motivate the assumptions made in heuristic models. In our model, the priors formalize the belief that a certain behavior is a regularity. The evidence is provided by other group members’ behavior and the likelihood by their reliability. We implement the model in a series of computer simulations and examine the group-level outcomes. We claim that domain-general belief revision helps explain why we look for regularities in social life in the first place. We argue that it is the disposition to look for regularities and react to them that generates descriptive norms. In our search for rules, we create them. more...

Life-science phenomena are often explained by specifying the mechanisms that bring them about. The new mechanistic philosophers have done much to substantiate this claim, and to provide us with a better understanding of what mechanisms are and how they explain. While there is disagreement among current mechanists on various issues, they share a common core position and a seeming commitment to some form of scientific realism. But is such a commitment necessary? Is it the best way to go about mechanistic explanation? In this paper, we propose an alternative antirealist account that also fits explanatory practice in the life sciences. We pay special attention to mechanistic models, i.e. scientific models that involve a mechanism, and to the role of coherence considerations in building such models. To illustrate our points, we consider the mechanism for the action potential. more...

A descriptive norm is a behavioral rule that individuals follow when their empirical expectations of others following the same rule are met. We aim to provide an account of the emergence of descriptive norms by first looking at a simple case, that of the standing ovation. We examine the structure of a standing ovation, and show it can be generalized to describe the emergence of a wide range of descriptive norms. more...

Emulating spiking neural networks on analog neuromorphic hardware offers several advantages over simulating them on conventional computers, particularly in terms of speed and energy consumption. However, this usually comes at the cost of reduced control over the dynamics of the emulated networks. In this paper, we demonstrate how iterative training of a hardware-emulated network can compensate for anomalies induced by the analog substrate. We first convert a deep neural network trained in software to a spiking network on the BrainScaleS wafer-scale neuromorphic system, thereby enabling an acceleration factor of 10 000 compared to the biological time domain. This mapping is followed by the in-the-loop training, where in each training step, the network activity is first recorded in hardware and then used to compute the parameter updates in software via backpropagation. An essential finding is that the parameter updates do not have to be precise, but only need to approximately follow the correct gradient, which simplifies the computation of updates. Using this approach, after only several tens of iterations, the spiking network shows an accuracy close to the ideal software-emulated prototype. The presented techniques show that deep spiking networks emulated on analog neuromorphic devices can attain good computational performance despite the inherent variations of the analog substrate., 8 pages, 10 figures, submitted to IJCNN 2017 more...

We provide a Bayesian justification of the idea that, under certain conditions, the absence of an argument in favour of the truth of a hypothesis H constitutes a good argument against the truth of H. more...

Despite being originally inspired by the central nervous system, artificial neural networks have diverged from their biological archetypes as they have been remodeled to fit particular tasks. In this paper, we review several possibilites to reverse map these architectures to biologically more realistic spiking networks with the aim of emulating them on fast, low-power neuromorphic hardware. Since many of these devices employ analog components, which cannot be perfectly controlled, finding ways to compensate for the resulting effects represents a key challenge. Here, we discuss three different strategies to address this problem: the addition of auxiliary network components for stabilizing activity, the utilization of inherently robust architectures and a training method for hardware-emulated networks that functions without perfect knowledge of the system's dynamics and parameters. For all three scenarios, we corroborate our theoretical considerations with experimental results on accelerated analog neuromorphic platforms., Comment: accepted at ISCAS 2017 more...

Toy models are highly idealized and extremely simple models. Although they are omnipresent across scientific disciplines, toy models are a surprisingly under-appreciated subject in the philosophy of science. The main philosophical puzzle regarding toy models concerns what the epistemic goal of toy modelling is. One promising proposal for answering this question is the claim that the epistemic goal of toy models is to provide individual scientists with understanding. The aim of this article is to precisely articulate and to defend this claim. In particular, we will distinguish between autonomous and embedded toy models, and then argue that important examples of autonomous toy models are sometimes best interpreted to provide how-possibly understanding, while embedded toy models yield how-actually understanding, if certain conditions are satisfied. more...

Various scientific theories stand in a reductive relation to each other. In a recent article, we have argued that a generalized version of the Nagel-Schaffner model (GNS) is the right account of this relation. In this article, we present a Bayesian analysis of how GNS impacts on confirmation. We formalize the relation between the reducing and the reduced theory before and after the reduction using Bayesian networks, and thereby show that, post-reduction, the two theories are confirmatory of each other. We then ask when a purported reduction should be accepted on epistemic grounds. To do so, we compare the prior and posterior probabilities of the conjunction of both theories before and after the reduction and ask how well each is confirmed by the available evidence. more...

We provide welfarist evaluations of decision rules for federations of states and consider models, under which the interests of people from different states are stochastically dependent. We concentrate on two welfarist standards, viz. that the expected average utility for a person in the federation be maximized or that the expected utilities for the different people be equal. We discuss an analytical result that characterizes the decision rule with maximum expected average utility, set up a class of models that display interstate dependencies and run simulations for different dependency scenarios in the European Union. We find that the results that Beisbart and Bovens (Soc Choice Welf 29:581–608, 2007) established for two types of models without interstate dependencies are fairly stable if interstate dependencies are switched on. There are exceptions, though: sometimes the way in which alternative decision rules shape the welfare distribution is significantly affected by such dependencies. These exceptions particularly include cases in which the interests of people from different states are partly anti-correlated. more...

We present a study of the spreading of trends in artificial social influence networks using agent based models. We concentrate on basic properties of the agents which describe their individual attitudes towards a trend, as well as the influence which they exert in their social neighbourhood. Using a simple random network, we investigate the impact of network dynamicity, situations of opposing trends, and the disappearance of trends. A 'community' network is used to study the impact of group cohesiveness and connectors for the spreading of trends in social communities. more...

Zusammenfassung Der Beitrag verbindet die Daten aktueller DSB-Bestandserhebungen und der 10. koordinierten Bevölkerungsvorausberechnung des Statistischen Bundesamtes zu einer interdisziplinären Studie über die voraussichtliche Mitgliederentwicklung des organisierten Sports. Durch die Berücksichtigung der derzeit denkbaren Minimal- und Maximalvarianten soll dabei der Einfluss des demografischen Wandels auf die Sportentwicklung empirisch eingegrenzt werden. Ziel ist es, sowohl absolute als auch altersstrukturelle Konsequenzen für die Zukunft des DOSB aufzuzeigen. Sich abzeichnende Chancen, Risiken und Ressourcen werden hierbei gesondert hervorgehoben und auf entsprechende Forderungen an den organisierten Sport abgeleitet. more...

In the past few years, there has been an increasing tendency in the application of formal and experimentalmethods to tackle philosophical issues.Weverymuch approve of this trend,whichweviewas part and parcel of the recent renewal of “scientific philosophy”: In our mind, the aim of a scientifically oriented philosophy is to adopt formal and experimental methods to address philosophical questions. A distinguishing feature of contemporary scientific philosophy is that the use of formal and experimental methods is not confined to areas such as the philosophy of science, of mathematics, or of physics. Quite the contrary: This research program applies its broad toolkit of formal and experimental practices to a very large range of philosophical areas. For instance, in the philosophy of cognitive science, the development ofmathematicalmodels of concepts representation has proved to be an innovative way to compare normative theories against empirical results. In the philosophy of economics, agent-based models have been used to explore the notion of causality used in economics. More generally, different areas of philosophy—from the philosophy of language to the philosophy of cognitive science, and from ethics to the philosophy of economics—have become increasingly scientific and characterized by a highly interdisciplinary approach. In tandem with this methodological turn, the dispute about whether philosophy should appeal to formal or experimental methods has made a comeback: Experimental philosophers defend the use of empirical methods as a means of exploring more...

A coherent story is a story that fits together well. This notion plays a central role in the coherence theory of justification and has been proposed as a criterion for scientific theory choice. Many attempts have been made to give a probabilistic account of this notion. A proper account of coherence must not start from some partial intuitions, but should pay attention to the role that this notion is supposed to play within a particular context. Coherence is a property of an information set that boosts our confidence that its content is true ceteris paribus when we receive information from independent and partially reliable sources. We construct a measure cr that relies on hypothetical sources with certain idealized characteristics. A maximally coherent information set, that is, a set with equivalent propositions, affords a maximal confidence boost. cr is the ratio of the actual confidence boost over the confidence boost that we would have received, had the information been presented in the form of maximally coherent information, ceteris paribus. This measure is functionally dependent on the degree of reliability r of the sources. We use cr to construct a coherence quasi‐ordering over information sets S and S′: S is no less coherent than S′ just in case cr(S) is not smaller than cr(S′) for any value of the reliability parameter. We show that, on our account, the coherence of the story about the world gives us a reason to believe that the story is true and that the coherence of a scientific theory, construed as a set of models, is a proper criterion for theory choice. more...

Philosophy, perhaps more than any other academic discipline, likes to reflect upon itself. Thus, it is no surprise that philosophers regularly ask questions such as: What is the scope of philosophy, what are its important questions, and what are the proper methods to address them? Asking these questions also means to take stock and to enquire where the discipline is going. This is an especially worthwhile activity in contemporary philosophy of science as this field has been changing rapidly since its institutional consolidation in the 1950s. For present purposes we may very roughly, but still usefully, describe this change as having three phases. In the first phase, which lasted until the mid 1960s, philosophy of science was dominated by Logical Empiricism and formal approaches to philosophically analyzing science. The second phase began in the late 1960s and lasted until the second half of the 1980s. It brought the naturalistic turn, a critique of the Logical Empiricist’s picture of science as too far away from the actual practice of science, a focus on the history and the social structure of science, a shift from theories as the primary target of philosophical analysis to models and experimental practices, and many detailed case studies. While the Logical Empiricists gave us a grand general picture of science, the naturalists’ working assumption has been that aiming at such a picture underappreciates the complexity and diversity of real science. Moreover, the naturalists moved normative questions into the background. In the third more...

It is often claimed that the greatest value of the Bayesian framework in cognitive science consists in its unifying power. Several Bayesian cognitive scientists assume that unification is obviously linked to explanatory power. But this link is not obvious, as unification in science is a heterogeneous notion, which may have little to do with explanation. While a crucial feature of most adequate explanations in cognitive science is that they reveal aspects of the causal mechanism that produces the phenomenon to be explained, the kind of unification afforded by the Bayesian framework to cognitive science does not necessarily reveal aspects of a mechanism. Bayesian unification, nonetheless, can place fruitful constraints on causal-mechanical explanation. more...

The design of integrated circuits has achieved a great deal of attention in the last decade. In the routing phase, there have survived two unsolved layout problems that are important from both the theoretical and the practical point of view. Up to now, switchbox routing has been known to be solvable in polynomial time when there are only 2-terminal nets, and to be NP-complete in case there exist nets involving at least five terminals. Our main result is that this problem is NP-complete even if no net has more than three terminals. Hence, from the theoretical perspective, the switchbox routing problem is completely settled.The NP-completeness proof is based on a reduction from a special kind of the satisfiability problem. It also is possible to adopt our construction to channel routing implying that this problem is NP-complete, even if each net does not consist of more than five terminals. This improves upon a result of Sarrafzadeh who proved the NP-completeness in case of nets with no more than six terminals. more...