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  1. Sample logic.Matthias Gerner - 2022 - Logic Journal of the IGPL 30 (5):728-776.
    The need for a ‘many-valued logic’ in linguistics has been evident since the 1970s, but there was lack of clarity as to whether it should come from the family of fuzzy logics or from the family of probabilistic logics. In this regard, Fine [14] and Kamp [26] pointed out undesirable effects of fuzzy logic (the failure of idempotency and coherence) which kept two generations of linguists and philosophers at arm’s length. (Another unwanted feature of fuzzy logic is the property of (...)
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  • The in-principle inconclusiveness of causal evidence in macroeconomics.Tobias Henschen - 2018 - European Journal for Philosophy of Science 8 (3):709-733.
    The paper analyzes the methods that macroeconomists can use to provide evidence in support of causal hypotheses: the instrumental variable method and econometric causality tests. It argues that the evidence that macroeconomists provide when using these methods is in principle too inconclusive to support the hypothesis that X directly type-level causes Y, where X and Y stand for macroeconomic aggregates like the real interest rate and aggregate demand. The evidence provided by the IV method is too inconclusive because it derives (...)
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  • Trust and the value of overconfidence: a Bayesian perspective on social network communication.Aron Vallinder & Erik J. Olsson - 2014 - Synthese 191 (9):1991-2007.
    The paper presents and defends a Bayesian theory of trust in social networks. In the first part of the paper, we provide justifications for the basic assumptions behind the model, and we give reasons for thinking that the model has plausible consequences for certain kinds of communication. In the second part of the paper we investigate the phenomenon of overconfidence. Many psychological studies have found that people think they are more reliable than they actually are. Using a simulation environment that (...)
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  • A comparison of three Occam’s razors for Markovian causal models.Jiji Zhang - 2013 - British Journal for the Philosophy of Science 64 (2):423-448.
    The framework of causal Bayes nets, currently influential in several scientific disciplines, provides a rich formalism to study the connection between causality and probability from an epistemological perspective. This article compares three assumptions in the literature that seem to constrain the connection between causality and probability in the style of Occam's razor. The trio includes two minimality assumptions—one formulated by Spirtes, Glymour, and Scheines (SGS) and the other due to Pearl—and the more well-known faithfulness or stability assumption. In terms of (...)
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  • Reversing 30 years of discussion: why causal decision theorists should one-box.Wolfgang Spohn - 2012 - Synthese 187 (1):95-122.
    The paper will show how one may rationalize one-boxing in Newcomb's problem and drinking the toxin in the Toxin puzzle within the confines of causal decision theory by ascending to so-called reflexive decision models which reflect how actions are caused by decision situations (beliefs, desires, and intentions) represented by ordinary unreflexive decision models.
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  • Dependency Equilibria and the Causal Structure of Decision and Game Situation.Wolfgang Spohn - unknown
    The paper attempts to rationalize cooperation in the one-shot prisoners' dilemma (PD). It starts by introducing (and preliminarily investigating) a new kind of equilibrium (differing from Aumann's correlated equilibria) according to which the players' actions may be correlated (sect. 2). In PD the Pareto-optimal among these equilibria is joint cooperation. Since these equilibria seem to contradict causal preconceptions, the paper continues with a standard analysis of the causal structure of decision situations (sect. 3). The analysis then raises to a reflexive (...)
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  • Causal laws are objectifications of inductive schemes.Wolfgang Spohn - 1955 - In Anthony Eagle (ed.), Philosophy of Probability. Routledge. pp. 223-252.
    And this paper is an attempt to say precisely how, thus addressing a philosophical problem which is commonly taken to be a serious one. It does so, however, in quite an idiosyncratic way. It is based on the account of inductive schemes I have given in (1988) and (1990a) and on the conception of causation I have presented in (1980), (1983), and (1990b), and it intends to fill one of many gaps which have been left by these papers. Still, I (...)
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  • Ranking Functions and Rankings on Languages.Franz Huber - 2006 - Artificial Intelligence 170 (4-5):462-471.
    The Spohnian paradigm of ranking functions is in many respects like an order-of-magnitude reverse of subjective probability theory. Unlike probabilities, however, ranking functions are only indirectly—via a pointwise ranking function on the underlying set of possibilities W —defined on a field of propositions A over W. This research note shows under which conditions ranking functions on a field of propositions A over W and rankings on a language L are induced by pointwise ranking functions on W and the set of (...)
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  • Direct and indirect causes.Wolfgang Spohn - 1990 - Topoi 9 (2):125-145.
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  • Against modularity, the causal Markov condition, and any link between the two: Comments on Hausman and Woodward.Nancy Cartwright - 2002 - British Journal for the Philosophy of Science 53 (3):411-453.
    In their rich and intricate paper ‘Independence, Invariance, and the Causal Markov Condition’, Daniel Hausman and James Woodward ([1999]) put forward two independent theses, which they label ‘level invariance’ and ‘manipulability’, and they claim that, given a specific set of assumptions, manipulability implies the causal Markov condition. These claims are interesting and important, and this paper is devoted to commenting on them. With respect to level invariance, I argue that Hausman and Woodward's discussion is confusing because, as I point out, (...)
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  • A dynamic interaction between machine learning and the philosophy of science.Jon Williamson - 2004 - Minds and Machines 14 (4):539-549.
    The relationship between machine learning and the philosophy of science can be classed as a dynamic interaction: a mutually beneficial connection between two autonomous fields that changes direction over time. I discuss the nature of this interaction and give a case study highlighting interactions between research on Bayesian networks in machine learning and research on causality and probability in the philosophy of science.
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  • Toward a synthesis of deterministic and probabilistic formulations of causal relations by the functional relation concept.Stanley A. Mulaik - 1986 - Philosophy of Science 53 (3):313-332.
    There have been two principal paradigms for the formulation of the causal relation--logical implication and functional relationship. In this paper, I present a case for preferring the functional relationship formulation and then discuss how the functional relationship formulation may be implemented in the probabilistic case in a manner analogous to the way others have implemented the logical implication formulation in the probabilistic case. I show how the "local independence" assumption found in many models used in the behavioral and social sciences (...)
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  • Bayes Nets and Rationality.Stephan Hartmann - 2021 - In Markus Knauff & Wolfgang Spohn (eds.), The Handbook of Rationality. London: MIT Press.
    Bayes nets are a powerful tool for researchers in statistics and artificial intelligence. This chapter demonstrates that they are also of much use for philosophers and psychologists interested in (Bayesian) rationality. To do so, we outline the general methodology of Bayes nets modeling in rationality research and illustrate it with several examples from the philosophy and psychology of reasoning and argumentation. Along the way, we discuss the normative foundations of Bayes nets modeling and address some of the methodological problems it (...)
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  • Quantifying proportionality and the limits of higher-level causation and explanation.Alexander Gebharter & Markus Ilkka Eronen - 2023 - British Journal for the Philosophy of Science 74 (3):573-601.
    Supporters of the autonomy of higher-level causation (or explanation) often appeal to proportionality, arguing that higher-level causes are more proportional than their lower-level realizers. Recently, measures based on information theory and causal modeling have been proposed that allow one to shed new light on proportionality and the related notion of specificity. In this paper we apply ideas from this literature to the issue of higher vs. lower-level causation (and explanation). Surprisingly, proportionality turns out to be irrelevant for the question of (...)
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  • Bayesian Nets Are All There Is To Causal Dependence.Wolfgang Spohn - unknown
    The paper displays the similarity between the theory of probabilistic causation developed by Glymour et al. since 1983 and mine developed since 1976: the core of both is that causal graphs are Bayesian nets. The similarity extends to the treatment of actions or interventions in the two theories. But there is also a crucial difference. Glymour et al. take causal dependencies as primitive and argue them to behave like Bayesian nets under wide circumstances. By contrast, I argue the behavior of (...)
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  • On the Properties of Conditional Independence.Wolfgang Spohn - 1994 - In Paul Humphreys (ed.), Patrick Suppes, Scientific Philosopher Vol. 1: Probability and Probabilistic Causality. Kluwer Academic Publishers.
    As the paper explains, it is crucial to epistemology in general and to the theory of causation in particular to investigate the properties of conditional independence as completely as possible. The paper summarizes the most important results concerning conditional independence with respect to two important representations of epistemic states, namely (strictly positive) probability measures and natural conditional (or disbelief or ranking) functions. It finally adds some new observations.
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  • Qualitative probabilities for default reasoning, belief revision, and causal modeling.Moisés Goldszmidt & Judea Pearl - 1996 - Artificial Intelligence 84 (1-2):57-112.
    This paper presents a formalism that combines useful properties of both logic and probabilities. Like logic, the formalism admits qualitative sentences and provides symbolic machinery for deriving deductively closed beliefs and, like probability, it permits us to express if-then rules with different levels of firmness and to retract beliefs in response to changing observations. Rules are interpreted as order-of-magnitude approximations of conditional probabilities which impose constraints over the rankings of worlds. Inferences are supported by a unique priority ordering on rules (...)
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  • Causation: An alternative.Wolfgang Spohn - 2006 - British Journal for the Philosophy of Science 57 (1):93-119.
    The paper builds on the basically Humean idea that A is a cause of B iff A and B both occur, A precedes B, and A raises the metaphysical or epistemic status of B given the obtaining circumstances. It argues that in pursuit of a theory of deterministic causation this ‘status raising’ is best explicated not in regularity or counterfactual terms, but in terms of ranking functions. On this basis, it constructs a rigorous theory of deterministic causation that successfully deals (...)
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  • Bayesian Networks and the Problem of Unreliable Instruments.Luc Bovens & Stephan Hartmann - 2002 - Philosophy of Science 69 (1):29-72.
    We appeal to the theory of Bayesian Networks to model different strategies for obtaining confirmation for a hypothesis from experimental test results provided by less than fully reliable instruments. In particular, we consider (i) repeated measurements of a single test consequence of the hypothesis, (ii) measurements of multiple test consequences of the hypothesis, (iii) theoretical support for the reliability of the instrument, and (iv) calibration procedures. We evaluate these strategies on their relative merits under idealized conditions and show some surprising (...)
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  • Causal concepts and temporal ordering.Reuben Stern - 2019 - Synthese 198 (Suppl 27):6505-6527.
    Though common sense says that causes must temporally precede their effects, the hugely influential interventionist account of causation makes no reference to temporal precedence. Does common sense lead us astray? In this paper, I evaluate the power of the commonsense assumption from within the interventionist approach to causal modeling. I first argue that if causes temporally precede their effects, then one need not consider the outcomes of interventions in order to infer causal relevance, and that one can instead use temporal (...)
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  • Axioms of causal relevance.David Galles & Judea Pearl - 1997 - Artificial Intelligence 97 (1-2):9-43.
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  • On the relationship between individual and population health.Onyebuchi A. Arah - 2009 - Medicine, Health Care and Philosophy 12 (3):235-244.
    The relationship between individual and population health is partially built on the broad dichotomization of medicine into clinical medicine and public health. Potential drawbacks of current views include seeing both individual and population health as absolute and independent concepts. I will argue that the relationship between individual and population health is largely relative and dynamic. Their interrelated dynamism derives from a causally defined life course perspective on health determination starting from an individual’s conception through growth, development and participation in the (...)
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  • Causation, Coherence and Concepts : a Collection of Essays.Wolfgang Spohn - unknown
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  • The 5 Questions.Wolfgang Spohn - 2005 - In Vincent F. Hendricks & John Symons (eds.), Formal Philosophy. Automatic Press/VIP.
    "Five Questions on Formal Philosophy": Like the other authors in the volume, I was asked for my reflections on the character of philosophy by answering the following five questions : 1. Why were you initially drawn to formal methods? 2. What example from your work illustrates the role formal methods can play in philosophy? 3. What is the proper role of philosophy in relation to other disciplines? 4. What do you consider the most neglected topics and/or contributions in late 20th (...)
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  • On Reichenbach's Principle of the Common Cause.Wolfgang Spohn - unknown
    This paper deals with Hans Reichenbach's common cause principle. It was propounded by him in, and has been developed and widely applied by Wesley Salmon, e.g. in and. Thus, it has become one of the focal points of the continuing discussion of causation. The paper addresses five questions. Section 1 asks: What does the principle say? And section 2 asks: What is its philosophical significance? The most important question, of course, is this: Is the principle true? To answer that question, (...)
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  • Counterfactuals and Causal Models: Introduction to the Special Issue.Steven A. Sloman - 2013 - Cognitive Science 37 (6):969-976.
    Judea Pearl won the 2010 Rumelhart Prize in computational cognitive science due to his seminal contributions to the development of Bayes nets and causal Bayes nets, frameworks that are central to multiple domains of the computational study of mind. At the heart of the causal Bayes nets formalism is the notion of a counterfactual, a representation of something false or nonexistent. Pearl refers to Bayes nets as oracles for intervention, and interventions can tell us what the effect of action will (...)
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  • Reward versus risk in uncertain inference: Theorems and simulations.Gerhard Schurz & Paul D. Thorn - 2012 - Review of Symbolic Logic 5 (4):574-612.
    Systems of logico-probabilistic reasoning characterize inference from conditional assertions that express high conditional probabilities. In this paper we investigate four prominent LP systems, the systems _O, P_, _Z_, and _QC_. These systems differ in the number of inferences they licence _. LP systems that license more inferences enjoy the possible reward of deriving more true and informative conclusions, but with this possible reward comes the risk of drawing more false or uninformative conclusions. In the first part of the paper, we (...)
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  • Deterministic and probabilistic reasons and causes.Wolfgang Spohn - 1983 - Erkenntnis 19 (1-3):371 - 396.
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  • Believing more, risking less: On coherence, truth and non-trivial extensions.Luc Bovens & Erik J. Olsson - 2002 - Erkenntnis 57 (2):137 - 150.
    If you believe more things you thereby run a greater risk of being in error than if you believe fewer things. From the point of view of avoiding error, it is best not to believe anything at all, or to have very uncommitted beliefs. But considering the fact that we all in fact do entertain many specific beliefs, this recommendation is obviously in flagrant dissonance with our actual epistemic practice. Let us call the problem raised by this apparent conflict the (...)
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  • Reply to Jim Woodward’s Comments on Wolfgang Spohn’s Laws of Belief.Wolfgang Spohn - 2019 - Philosophy of Science 86 (4):773-784.
    This is one of a pair of discussion notes comparing some features of the account of causation in Wolfgang Spohn’s Laws of Belief with the “interventionist” account in James Woodward’s Making Things Happen. This note locates the core difference of the accounts in the fact that Woodward’s account follows an epistemological order, while Spohn’s follows a conceptual order. This unfolds in five further differences: type- versus token-level causation, reference to time, actual/counterfactual intervention versus epistemic/suppositional wiggling, a circular versus a circle-free (...)
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  • Die Verursachung der Vergangenheit: Zur Debatte um die Möglichkeit rückwirkender Kausalität.Christian Hugo Hoffmann - 2021 - Deutsche Zeitschrift für Philosophie 69 (6):950-982.
    How can a present or future event causally influence one in the past? Even though the case of such a relationship is often quickly dismissed as impossible, this paper suggests that this reaction is hasty and omits interesting as well as substantive arguments and considerations. In an introductory synopsis of the metaphysics of causality, we first present and discuss arguments for and against the possibility of backwards causation. On the other hand, we suggest that a probabilistic notion of causality according (...)
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