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  1. Horacio Arló-Costa (2001). Bayesian Epistemology and Epistemic Conditionals. Journal of Philosophy 98 (11):555-593.
    The notion of probability occupies a central role in contemporary epistemology and cognitive science. Nevertheless, the classical notion of probability is hard to reconcile with the central notions postulated by the epistemological tradition.
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  2. Horacio Arlo-Costa & Arthur Paul Pedersen, Social Norms, Rational Choice and Belief Change.
    This article elaborates on foundational issues in the social sciences and their impact on the contemporary theory of belief revision. Recent work in the foundations of economics has focused on the role external social norms play in choice. Amartya Sen has argued in [Sen93] that the traditional rationalizability approach used in the theory of rational choice has serious problems accommodating the role of social norms. Sen's more recent work [Sen96, Sen97] proposes how one might represent social norms in the theory (...)
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  3. Alexandru Baltag & Sonja Smets (2008). Probabilistic Dynamic Belief Revision. Synthese 165 (2):179 - 202.
    We investigate the discrete (finite) case of the Popper–Renyi theory of conditional probability, introducing discrete conditional probabilistic models for knowledge and conditional belief, and comparing them with the more standard plausibility models. We also consider a related notion, that of safe belief, which is a weak (non-negatively introspective) type of “knowledge”. We develop a probabilistic version of this concept (“degree of safety”) and we analyze its role in games. We completely axiomatize the logic of conditional belief, knowledge and safe belief (...)
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  4. Richard Baron (2013). The Laws of Belief by Wolfgang Spohn. Philosophy Now 94:42-43.
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  5. Pierpaolo Battigalli & Giacomo Bonanno (1997). The Logic of Belief Persistence. Economics and Philosophy 13 (1):39-59.
    The principle of belief persistence, or conservativity principle, states that ’\Nhen changing beliefs in response to new evidence, you should continue to believe as many of the old beliefs as possible' (Harman, 1986, p. 46). In particular, this means that if an individual gets new information, she has to accommodate it in her new belief set (the set of propositions she believes), and, if the new information is not inconsistent with the old belief set, then (1) the individual has to (...)
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  6. Stefano Bigliardi (2010). Wolfgang Spohn and the Ranking Functions Theory. Rivista di Filosofia 101 (1):57-80.
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  7. Alexander Bochman (2001). A Logical Theory of Nonmonotonic Inference and Belief Change. Springer.
    This is the first book that integrates nonmonotonic reasoning and belief change into a single framework from an artificial intelligence logic point-of-view.
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  8. Giacomo Bonanno (2005). A Simple Modal Logic for Belief Revision. Synthese 147 (2):193 - 228.
    We propose a modal logic based on three operators, representing intial beliefs, information and revised beliefs. Three simple axioms are used to provide a sound and complete axiomatization of the qualitative part of Bayes’ rule. Some theorems of this logic are derived concerning the interaction between current beliefs and future beliefs. Information flows and iterated revision are also discussed.
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  9. R. D. Bradley (1963). Quixotic Reasoning: A Rejoinder to K. W. Ranking. Australasian Journal of Philosophy 41 (3):362 – 372.
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  10. Richard Bradley (2009). Revising Incomplete Attitudes. Synthese 171 (2):235 - 256.
    Bayesian models typically assume that agents are rational, logically omniscient and opinionated. The last of these has little descriptive or normative appeal, however, and limits our ability to describe how agents make up their minds (as opposed to changing them) or how they can suspend or withdraw their opinions. To address these limitations this paper represents the attitudinal states of non-opinionated agents by sets of (permissible) probability and desirability functions. Several basic ways in which such states of mind can be (...)
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  11. Samir Chopra, Aditya Ghose & Thomas Meyer (2003). Non-Prioritized Ranked Belief Change. Journal of Philosophical Logic 32 (4):417-443.
    Traditional accounts of belief change have been criticized for placing undue emphasis on the new belief provided as input. A recent proposal to address such issues is a framework for non-prioritized belief change based on default theories (Ghose and Goebel, 1998). A novel feature of this approach is the introduction of disbeliefs alongside beliefs which allows for a view of belief contraction as independently useful, instead of just being seen as an intermediate step in the process of belief revision. This (...)
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  12. G. Crocco, Luis Fariñas del Cerro & Andreas Herzig (eds.) (1995). Conditionals: From Philosophy to Computer Science. Oxford University Press.
    This book looks at the ways in which conditionals, an integral part of philosophy and logic, can be of practical use in computer programming. It analyzes the different types of conditionals, including their applications and potential problems. Other topics include defeasible logics, the Ramsey test, and a unified view of consequence relation and belief revision. Its implications will be of interest to researchers in logic, philosophy, and computer science, particularly artificial intelligence.
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  13. Franz Dietrich, Christian List & Richard Bradley, A Unified Characterization of Belief-Revision Rules.
    This paper characterizes several belief-revision rules in a unified framework: Bayesian revision upon learning some event, Jeffrey revision upon learning new probabilities of some events, Adams revision upon learning some new conditional probabilities, and 'dual-Jeffrey' revision upon learning a new conditional probability function. Despite their differences, these revision rules can be characterized in terms of the same two axioms: responsiveness, which requires that revised beliefs incorporate what has been learnt, and conservativeness, which requires that beliefs on which the learnt input (...)
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  14. Nir Friedman & Joseph Y. Halpern (1999). Belief Revision: A Critique. [REVIEW] Journal of Logic, Language and Information 8 (4):401-420.
    We examine carefully the rationale underlying the approaches to belief change taken in the literature, and highlight what we view as methodological problems. We argue that to study belief change carefully, we must be quite explicit about the ontology or scenario underlying the belief change process. This is something that has been missing in previous work, with its focus on postulates. Our analysis shows that we must pay particular attention to two issues that have often been taken for granted: the (...)
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  15. Andre Fuhrmann (1996). An Essay on Contraction. Center for the Study of Language and Inf.
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  16. D. Gabbay & P. Smets (eds.) (1998). Handbook of Defeasible Reasoning and Uncertainty Management Systems, Vol 3. Kluwer Academic Pub.
    HANDBOOK OF DEFEASIBLE REASONING AND UNCERTAINTY MANAGEMENT SYSTEMS EDITORS: DOV M. ... and A. Hunter Volume 3: Belief Change Edited by D. Dubois and H. Prade HANDBOOK OF DEFEASIBLE REASONING AND ...
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  17. Maria Carla Galavotti (2003). Harold Jeffreys' Probabilistic Epistemology: Between Logicism and Subjectivism. British Journal for the Philosophy of Science 54 (1):43-57.
    Harold Jeffreys' ideas on the interpretation of probability and epistemology are reviewed. It is argued that with regard to the interpretation of probability, Jeffreys embraces a version of logicism that shares some features of the subjectivism of Ramsey and de Finetti. Jeffreys also developed a probabilistic epistemology, characterized by a pragmatical and constructivist attitude towards notions such as ‘objectivity’, ‘reality’ and ‘causality’. 1 Introductory remarks 2 The interpretation of probability 3 Jeffreys' probabilistic epistemology.
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  18. Robinson A. Grover (1974). The Ranking Assumption. Theory and Decision 4 (3-4):277-299.
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  19. Sven Ove Hansson, Ten Philosophical Problems in Belief Revision.
    The paper introduces ten open problems in belief revision theory, related to the representation of the belief state, to different notions of degrees of belief, and to the nature of change operations. It is argued that these problems are all issues in philosopical logic, in the strong sense of requiring inputs from both logic and philosophy for their solution.
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  20. Sven Ove Hansson (2006). Coherence in Epistemology and Belief Revision. Philosophical Studies 128 (1):93 - 108.
    A general theory of coherence is proposed, in which systemic and relational coherence are shown to be interdefinable. When this theory is applied to sets of sentences, it turns out that logical closure obscures the distinctions that are needed for a meaningful analysis of coherence. It is concluded that references to “all beliefs” in coherentist phrases such as “all beliefs support each other” have to be modified so that merely derived beliefs are excluded. Therefore, in order to avoid absurd conclusions, (...)
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  21. Sven Ove Hansson (2004). Review of Hans Rott, Change, Choice and Inference: A Study of Belief Revision and Nonmonotonic Reasoning. [REVIEW] Studia Logica: An International Journal for Symbolic Logic 77:145-147.
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  22. Sven Ove Hansson (1992). In Defense of Base Contraction. Synthese 91 (3):239 - 245.
    In the most common approaches to belief dynamics, states of belief are represented by sets that are closed under logical consequence. In an alternative approach, they are represented by non-closed belief bases. This representation has attractive properties not shared by closed representations. Most importantly, it can account for repeated belief changes that have not yet been satisfactorily accounted for in the closed approach.
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  23. Sven Ove Hansson (1991). Belief Contraction Without Recovery. Studia Logica 50 (2):251 - 260.
    The postulate of recovery is commonly regarded to be the intuitively least compelling of the six basic Gärdenfors postulates for belief contraction. We replace recovery by the seemingly much weaker postulate of core-retainment, which ensures that if x is excluded from K when p is contracted, then x plays some role for the fact that K implies p. Surprisingly enough, core-retainment together with four of the other Gärdenfors postulates implies recovery for logically closed belief sets. Reasonable contraction operators without recovery (...)
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  24. Sven Ove Hansson, Eduardo Leopoldo Fermé, John Cantwell & Marcelo Alejandro Falappa (2001). Credibility Limited Revision. Journal of Symbolic Logic 66 (4):1581-1596.
    Five types of constructions are introduced for non-prioritized belief revision, i.e., belief revision in which the input sentence is not always accepted. These constructions include generalizations of entrenchment-based and sphere-based revision. Axiomatic characterizations are provided, and close interconnections are shown to hold between the different constructions.
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  25. Gilbert Harman, Epistemology as Methodology.
    What is distinctive about my views in epistemology? One thing is that my concern with epistemology is a concern with methodology. Furthermore, I reject psychologism about logic and reject the idea that deductive rules like modus ponens are in any way rules of inference. I accept a kind of methodological conservatism and reject methodological theories that appeal to special foundations, analytic truth, or a priori justification. Although I believe that there are significant practical aspects of theoretical reasoning, I reject the (...)
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  26. Stephan Hartmann & L. Bovens (2001). Belief Expansion, Contextual Fit and the Reliability of Information Sources. In AkmanV (ed.), Modeling and Using Context,. Springer.
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  27. Franz Huber (2013). Belief Revision I: The AGM Theory. Philosophy Compass 8 (7):604-612.
    Belief revision theory studies how an ideal doxastic agent should revise her beliefs when she receives new information. In part I I will first present the AGM theory of belief revision (Alchourrón & Gärdenfors & Makinson 1985). Then I will focus on the problem of iterated belief revisions.
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  28. Franz Huber (2013). Belief Revision II: Ranking Theory. Philosophy Compass 8 (7):613-621.
    Belief revision theory studies how an ideal doxastic agent should revise her beliefs when she receives new information. In part I, I have first presented the AGM theory of belief revision. Then I have focused on the problem of iterated belief revisions. In part II, I will first present ranking theory (Spohn 1988). Then I will show how it solves the problem of iterated belief revisions. I will conclude by sketching two areas of future research.
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  29. Mark Kaplan (1983). Decision Theory as Philosophy. Philosophy of Science 50 (4):549-577.
    Is Bayesian decision theory a panacea for many of the problems in epistemology and the philosophy of science, or is it philosophical snake-oil? For years a debate had been waged amongst specialists regarding the import and legitimacy of this body of theory. Mark Kaplan had written the first accessible and non-technical book to address this controversy. Introducing a new variant on Bayesian decision theory the author offers a compelling case that, while no panacea, decision theory does in fact have the (...)
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  30. Kevin Kelly, The Learning Power of Belief Revision.
    Belief revision theory aims to describe how one should change one’s beliefs when they are contradicted by newly input information. The guiding principle of belief revision theory is to change one’s prior beliefs as little as possible in order to maintain consistency with the new information. Learning theory focuses, instead, on learning power: the ability to arrive at true beliefs in a wide range of possible environments. The goal of this paper is to bridge the two approaches by providing a (...)
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  31. Jonathan L. Kvanvig (1994). A Critique of Van Fraassen's Voluntaristic Epistemology. Synthese 98 (2):325-348.
    Van Fraassen's epistemology is forged from two commitments, one to a type of Bayesianism and the other to what he terms voluntarism. Van Fraassen holds that if one is going to follow a rule in belief-revision, it must be a Bayesian rule, but that one does not need to follow a rule in order to be rational. It is argued that van Fraassen's arguments for rejecting non-Bayesian rules is unsound, and that his voluntarism is subject to a fatal dilemma arising (...)
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  32. Isaac Levi, Contraction and Informational Value.
    According to the approach made famous by Alchourrón, Gärdenfors and Makinson (1985), revision is a transformation K*h of a potential belief state K by adding h yielding another potential belief state.1 This AGM revision transformation is a composition of two other transformations: contraction and expansion. K*h = [K-~h]+h. This is the expansion by adding h of the contraction K-~h of K by removing ~h.
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  33. Sten Lindström & Wlodek Rabinowicz, Belief Change for Introspective Agents. Spinning Ideas, Electronic Essays Dedicated to Peter Gärdenfors on His Fiftieth Birthday.
  34. Sten Lindström & Wlodek Rabinowicz (1999). DDL Unlimited: Dynamic Doxastic Logic for Introspective Agents. [REVIEW] Erkenntnis 50 (2-3):353-385.
  35. Sten Lindström & Wlodek Rabinowicz (1998). Conditionals and the Ramsey Test. In D. Gabbay & P. Smets (eds.), Handbook of Defeasible Reasoning and Uncertainty Management Systems, Vol 3.
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  36. Sten Lindström & Wlodek Rabinowicz (1995). The Ramsey Test Revisited. In G. Crocco, L. Fariñas del Cerro & A. Herzig (eds.), Conditionals: From Philosophy to Computer Science. Oxford University Press. 131-182.
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  37. Sten Lindström & Wlodzimierz Rabinowicz (1992). Belief Revision, Epistemic Conditionals and the Ramsey Test. Synthese 91 (3):195 - 237.
    Epistemic conditionals have often been thought to satisfy the Ramsey test (RT): If A, then B is acceptable in a belief state G if and only if B should be accepted upon revising G with A. But as Peter Gärdenfors has shown, RT conflicts with the intuitively plausible condition of Preservation on belief revision. We investigate what happens if (a) RT is retained while Preservation is weakened, or (b) vice versa. We also generalize Gärdenfors' approach by treating belief revision (...)
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  38. Sten Lindström & Wlodzimierz Rabinowicz (1989). On Probabilistic Representation of Non-Probabilistic Belief Revision. Journal of Philosophical Logic 18 (1):69 - 101.
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  39. Hailin Liu, Value-Based Contraction: A Representation Result.
    Sven-Ove Hansson and Erik Olsson studied in [7] the logical properties of an operation of contraction first proposed by Isaac Levi in [10]. They provided a completeness result for the simplest version of contraction that they call Levicontraction but left open the problem of characterizing axiomatically the more complex operation of value-based contraction or saturatable contraction. In this paper we propose an axiomatization for this operation and prove a completeness result for it. We argue that the resulting operation is better (...)
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  40. Edwin D. Mares (2002). A Paraconsistent Theory of Belief Revision. Erkenntnis 56 (2):229 - 246.
    This paper presents a theory of belief revision that allows people to come tobelieve in contradictions. The AGM theory of belief revision takes revision,in part, to be consistency maintenance. The present theory replacesconsistency with a weaker property called coherence. In addition to herbelief set, we take a set of statements that she rejects. These two sets arecoherent if they do not overlap. On this theory, belief revision maintains coherence.
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  41. Eric Martin & Daniel Osherson (1997). Scientific Discovery Based on Belief Revision. Journal of Symbolic Logic 62 (4):1352-1370.
    Scientific inquiry is represented as a process of rational hypothesis revision in the face of data. For the concept of rationality, we rely on the theory of belief dynamics as developed in [5, 9]. Among other things, it is shown that if belief states are left unclosed under deductive logic then scientific theories can be expanded in a uniform, consistent fashion that allows inquiry to proceed by any method of hypothesis revision based on "kernel" contraction. In contrast, if belief states (...)
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  42. Lydia Mechtenberg (2004). The Stability Theory of Knowledge and Belief Revision: Comments on Rott. Erkenntnis 61 (2-3):495 - 507.
    In this commentary on Rotts paper Stability, Strength and Sensitivity: Converting Belief into Knowledge, I discuss two problems of the stability theory of knowledge which are pointed out by Rott. I conclude that these problems offer no reason for rejecting the stability theory, but might be grounds for deviating from the standard AGM account of belief revision which Rott presupposes.
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  43. Andrés Páez, The Epistemic Value of Explanation.
    In this paper I defend the idea that there is a sense in which it is meaningful and useful to talk about objective understanding, and that to characterize that notion it is necessary to formulate an account of explanation that makes reference to the beliefs and epistemic goals of the participants in a cognitive enterprise. Using the framework for belief revision developed by Isaac Levi, I analyze the conditions that information must fulfill to be both potentially explanatory and epistemically (...)
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  44. John L. Pollock & Anthony S. Gillies (2000). Belief Revision and Epistemology. Synthese 122 (1-2):69-92.
    Postulational approaches attempt to understand the dynamics of belief revision by appealing to no more than the set of beliefs held by an agent and the logical relations between them. It is argued there that such an approach cannot work. A proper account of belief revision must also appeal to the arguments supporting beliefs, and recognize that those arguments can be defeasible. If we begin with a mature epistemological theory that accommodates this, it can be seen that the belief revision (...)
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  45. John Pollock & Anthony Gillies (2000). ``Belief Revision and Epistemology&Quot. Synthese 122:69--92.
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  46. Dag Prawitz & Dag Westerståhl (eds.) (1994). Logic and Philosophy of Science in Uppsala. Kluwer.
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  47. Wlodek Rabinowicz & Sten Lindström (1994). How to Model Relational Belief Revision. In Dag Prawitz & Dag Westerståhl (eds.), Logic and Philosophy of Science in Uppsala. Kluwer.
    This is a short version of Lindström & Rabinowicz 1991.In earlier papers, we proposed a generalization of the AGM approach to belief revision. The proposal was to view belief revision as a relation rather than as a function on theories (or belief sets). Going relational means that one allows for several equally reasonable revisions of a theory with a given proposition. In the present paper, we show that the relational approach is the natural result of generalizing in a certain way (...)
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  48. Hans Rott (1999). Coherence and Conservatism in the Dynamics of Belief. Erkenntnis 50 (2-3):387-412.
    In this paper I discuss the foundations of a formal theory of coherent and conservative belief change that is (a) suitable to be used as a method for constructing iterated changes of belief, (b) sensitive to the history of earlier belief changes, and (c) independent of any form of dispositional coherence. I review various ways to conceive the relationship between the beliefs actually held by an agent and her belief change strategies (that also deal with potential belief sets), show the (...)
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  49. Hans Rott & Maurice Pagnucco (1999). Severe Withdrawal (and Recovery). Journal of Philosophical Logic 28 (5):501-547.
    The problem of how to remove information from an agent's stock of beliefs is of paramount concern in the belief change literature. An inquiring agent may remove beliefs for a variety of reasons: a belief may be called into doubt or the agent may simply wish to entertain other possibilities. In the prominent AGM framework for belief change, upon which the work here is based, one of the three central operations, contraction, addresses this concern (the other two deal with the (...)
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  50. Ran Spiegler (2001). Inferring a Linear Ordering Over a Power Set. Theory and Decision 51 (1):31-49.
    An observer attempts to infer the unobserved ranking of two ideal objects, A and B, from observed rankings in which these objects are `accompanied' by `noise' components, C and D. In the first ranking, A is accompanied by C and B is accompanied by D, while in the second ranking, A is accompanied by D and B is accompanied by C. In both rankings, noisy-A is ranked above noisy-B. The observer infers that ideal-A is ranked above ideal-B. This commonly used (...)
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