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  1. Knowledge and Belief: An Introduction to the Logic of the Two Notions.Jaakko Hintikka - 1962 - Studia Logica 16:119-122.
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  • In Epistemic Networks, is Less Really More?Sarita Rosenstock, Cailin O'Connor & Justin Bruner - 2017 - Philosophy of Science 84 (2):234-252.
    We show that previous results from epistemic network models showing the benefits of decreased connectivity in epistemic networks are not robust across changes in parameter values. Our findings motivate discussion about whether and how such models can inform real-world epistemic communities. As we argue, only robust results from epistemic network models should be used to generate advice for the real-world, and, in particular, decreasing connectivity is a robustly poor recommendation.
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  • Logical Dynamics of Information and Interaction.Johan van Benthem - 2011 - New York: Cambridge University Press.
    This book develops a view of logic as a theory of information-driven agency and intelligent interaction between many agents - with conversation, argumentation and games as guiding examples. It provides one uniform account of dynamic logics for acts of inference, observation, questions and communication, that can handle both update of knowledge and revision of beliefs. It then extends the dynamic style of analysis to include changing preferences and goals, temporal processes, group action and strategic interaction in games. Throughout, the book (...)
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  • On Logics of Knowledge and Belief.Robert Stalnaker - 2006 - Philosophical Studies 128 (1):169-199.
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  • The Epistemic Benefit of Transient Diversity.Kevin J. S. Zollman - 2010 - Erkenntnis 72 (1):17-35.
    There is growing interest in understanding and eliciting division of labor within groups of scientists. This paper illustrates the need for this division of labor through a historical example, and a formal model is presented to better analyze situations of this type. Analysis of this model reveals that a division of labor can be maintained in two different ways: by limiting information or by endowing the scientists with extreme beliefs. If both features are present however, cognitive diversity is maintained indefinitely, (...)
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  • Pluralistic ignorance in the bystander effect: informational dynamics of unresponsive witnesses in situations calling for intervention.Rasmus Kraemmer Rendsvig - 2014 - Synthese 191 (11):2471-2498.
    The goal of the present paper is to construct a formal explication of the pluralistic ignorance explanation of the bystander effect. The social dynamics leading to inaction is presented, decomposed, and modeled using dynamic epistemic logic augmented with ‘transition rules’ able to characterize agent behavior. Three agent types are defined: First Responders who intervene given belief of accident; City Dwellers, capturing ‘apathetic urban residents’ and Hesitators, who observe others when in doubt, basing subsequent decision on social proof. It is shown (...)
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  • Logical dynamics of belief change in the community.Fenrong Liu, Jeremy Seligman & Patrick Girard - 2014 - Synthese 191 (11):2403-2431.
    In this paper we explore the relationship between norms of belief revision that may be adopted by members of a community and the resulting dynamic properties of the distribution of beliefs across that community. We show that at a qualitative level many aspects of social belief change can be obtained from a very simple model, which we call ‘threshold influence’. In particular, we focus on the question of what makes the beliefs of a community stable under various dynamical situations. We (...)
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  • Dynamic Update with Probabilities.Johan van Benthem, Jelle Gerbrandy & Barteld Kooi - 2009 - Studia Logica 93 (1):67 - 96.
    Current dynamic-epistemic logics model different types of information change in multi-agent scenarios. We generalize these logics to a probabilistic setting, obtaining a calculus for multi-agent update with three natural slots: prior probability on states, occurrence probabilities in the relevant process taking place, and observation probabilities of events. To match this update mechanism, we present a complete dynamic logic of information change with a probabilistic character. The completeness proof follows a compositional methodology that applies to a much larger class of dynamic-probabilistic (...)
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  • Network Epistemology: Communication in Epistemic Communities.Kevin J. S. Zollman - 2013 - Philosophy Compass 8 (1):15-27.
    Much of contemporary knowledge is generated by groups not single individuals. A natural question to ask is, what features make groups better or worse at generating knowledge? This paper surveys research that spans several disciplines which focuses on one aspect of epistemic communities: the way they communicate internally. This research has revealed that a wide number of different communication structures are best, but what is best in a given situation depends on particular details of the problem being confronted by the (...)
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  • Revising Beliefs Towards the Truth.Ilkka Niiniluoto - 2011 - Erkenntnis 75 (2):165-181.
    Belief revision (BR) and truthlikeness (TL) emerged independently as two research programmes in formal methodology in the 1970s. A natural way of connecting BR and TL is to ask under what conditions the revision of a belief system by new input information leads the system towards the truth. It turns out that, for the AGM model of belief revision, the only safe case is the expansion of true beliefs by true input, but this is not very interesting or realistic as (...)
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  • Knowledge and belief.Jaakko Hintikka - 1962 - Ithaca, N.Y.,: Cornell University Press.
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  • (6 other versions)The Structure of Scientific Revolutions.Thomas Samuel Kuhn - 1962 - Chicago: University of Chicago Press. Edited by Otto Neurath.
    A scientific community cannot practice its trade without some set of received beliefs. These beliefs form the foundation of the "educational initiation that prepares and licenses the student for professional practice". The nature of the "rigorous and rigid" preparation helps ensure that the received beliefs are firmly fixed in the student's mind. Scientists take great pains to defend the assumption that scientists know what the world is like...To this end, "normal science" will often suppress novelties which undermine its foundations. Research (...)
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  • The logic of justification.Sergei Artemov - 2008 - Review of Symbolic Logic 1 (4):477-513.
    We describe a general logical framework, Justification Logic, for reasoning about epistemic justification. Justification Logic is based on classical propositional logic augmented by justification assertions t: F that read t is a justification for F. Justification Logic absorbs basic principles originating from both mainstream epistemology and the mathematical theory of proofs. It contributes to the studies of the well-known Justified True Belief vs. Knowledge problem. We state a general Correspondence Theorem showing that behind each epistemic modal logic, there is a (...)
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  • Merging frameworks for interaction.Johan van Benthem, Jelle Gerbrandy, Tomohiro Hoshi & Eric Pacuit - 2009 - Journal of Philosophical Logic 38 (5):491-526.
    A variety of logical frameworks have been developed to study rational agents interacting over time. This paper takes a closer look at one particular interface, between two systems that both address the dynamics of knowledge and information flow. The first is Epistemic Temporal Logic (ETL) which uses linear or branching time models with added epistemic structure induced by agents’ different capabilities for observing events. The second framework is Dynamic Epistemic Logic (DEL) that describes interactive processes in terms of epistemic event (...)
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  • (6 other versions)The Structure of Scientific Revolutions.Thomas S. Kuhn - 1962 - Chicago, IL: University of Chicago Press. Edited by Ian Hacking.
    Thomas S. Kuhn's classic book is now available with a new index.
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  • (1 other version)The communication structure of epistemic communities.Kevin J. S. Zollman - 2007 - Philosophy of Science 74 (5):574-587.
    Increasingly, epistemologists are becoming interested in social structures and their effect on epistemic enterprises, but little attention has been paid to the proper distribution of experimental results among scientists. This paper will analyze a model first suggested by two economists, which nicely captures one type of learning situation faced by scientists. The results of a computer simulation study of this model provide two interesting conclusions. First, in some contexts, a community of scientists is, as a whole, more reliable when its (...)
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  • Epistemic Landscapes and the Division of Cognitive Labor.Michael Weisberg & Ryan Muldoon - 2009 - Philosophy of Science 76 (2):225-252.
    Because of its complexity, contemporary scientific research is almost always tackled by groups of scientists, each of which works in a different part of a given research domain. We believe that understanding scientific progress thus requires understanding this division of cognitive labor. To this end, we present a novel agent-based model of scientific research in which scientists divide their labor to explore an unknown epistemic landscape. Scientists aim to climb uphill in this landscape, where elevation represents the significance of the (...)
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  • The division of cognitive labor.Philip Kitcher - 1990 - Journal of Philosophy 87 (1):5-22.
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  • Dynamic Epistemic Logics of Diffusion and Prediction in Social Networks.Alexandru Baltag, Zoé Christoff, Rasmus K. Rendsvig & Sonja Smets - 2019 - Studia Logica 107 (3):489-531.
    We take a logical approach to threshold models, used to study the diffusion of opinions, new technologies, infections, or behaviors in social networks. Threshold models consist of a network graph of agents connected by a social relationship and a threshold value which regulates the diffusion process. Agents adopt a new behavior/product/opinion when the proportion of their neighbors who have already adopted it meets the threshold. Under this diffusion policy, threshold models develop dynamically towards a guaranteed fixed point. We construct a (...)
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  • (2 other versions)Modal Logic.Marcus Kracht - 2002 - Bulletin of Symbolic Logic 8 (2):299-301.
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  • Epistemic Logic and Information Update.A. Baltag, H. P. van Ditmarsch & L. S. Moss - 2008 - In P. Adriaans & J. van Benthem (eds.), hilosophy of Information. MIT Press.
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  • Dynamic logic for belief revision.Johan van Benthem - 2007 - Journal of Applied Non-Classical Logics 17 (2):129-155.
    We show how belief revision can be treated systematically in the format of dynamicepistemic logic, when operators of conditional belief are added. The core engine consists of definable update rules for changing plausibility relations between worlds, which have been proposed independently in the dynamic-epistemic literature on preference change. Our analysis yields two new types of modal result. First, we obtain complete logics for concrete mechanisms of belief revision, based on compositional reduction axioms. Next, we show how various abstract postulates for (...)
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  • Probabilistic dynamic epistemic logic.Barteld P. Kooi - 2003 - Journal of Logic, Language and Information 12 (4):381-408.
    In this paper I combine the dynamic epistemic logic ofGerbrandy (1999) with the probabilistic logic of Fagin and Halpern (1994). The resultis a new probabilistic dynamic epistemic logic, a logic for reasoning aboutprobability, information, and information change that takes higher orderinformation into account. Probabilistic epistemic models are defined, and away to build them for applications is given. Semantics and a proof systemis presented and a number of examples are discussed, including the MontyHall Dilemma.
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  • (1 other version)Modal Logic.Patrick Blackburn, Maarten de Rijke & Yde Venema - 2001 - Studia Logica 76 (1):142-148.
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  • Multi-agent Justification Logic: communication and evidence elimination. [REVIEW]Bryan Renne - 2012 - Synthese 185 (S1):43-82.
    This paper presents a logic combining Dynamic Epistemic Logic, a framework for reasoning about multi-agent communication, with a new multi-agent version of Justification Logic, a framework for reasoning about evidence and justification. This novel combination incorporates a new kind of multi-agent evidence elimination that cleanly meshes with the multi-agent communications from Dynamic Epistemic Logic, resulting in a system for reasoning about multi-agent communication and evidence elimination for groups of interacting rational agents.
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  • Dynamic Update with Probabilities.Johan Benthem, Jelle Gerbrandy & Barteld Kooi - 2009 - Studia Logica 93 (1):67-96.
    Current dynamic-epistemic logics model different types of information change in multi-agent scenarios. We generalize these logics to a probabilistic setting, obtaining a calculus for multi-agent update with three natural slots: prior probability on states, occurrence probabilities in the relevant process taking place, and observation probabilities of events. To match this update mechanism, we present a complete dynamic logic of information change with a probabilistic character. The completeness proof follows a compositional methodology that applies to a much larger class of dynamic-probabilistic (...)
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  • Probabilistic dynamic belief revision.Alexandru Baltag & Sonja Smets - 2008 - 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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  • Reasoning about information change.Jelle Gerbrandy & Willem Groeneveld - 1997 - Journal of Logic, Language and Information 6 (2):147-169.
    In this paper we introduce Dynamic Epistemic Logic, which is alogic for reasoning about information change in a multi-agent system. Theinformation structures we use are based on non-well-founded sets, and canbe conceived as bisimulation classes of Kripke models. On these structures,we define a notion of information change that is inspired by UpdateSemantics (Veltman, 1996). We give a sound and complete axiomatization ofthe resulting logic, and we discuss applications to the puzzle of the dirtychildren, and to knowledge programs.
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  • Logical Models of Informational Cascades.Alexandru Baltag, Zoé Christoff, Jens Ulrik Hansen & Sonja Smets - 2013 - In Johan Van Benthem & Fenrong Lui (eds.), Logic Across the University: Foundations and Applications. College Publications. pp. 405-432.
    In this paper, we investigate the social herding phenomenon known as informational cascades, in which sequential inter-agent communication might lead to epistemic failures at group level, despite availability of information that should be sufficient to track the truth. We model an example of a cascade, and check the correctness of the individual reasoning of each agent involved, using two alternative logical settings: an existing probabilistic dynamic epistemic logic, and our own novel logic for counting evidence. Based on this analysis, we (...)
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  • Science Bubbles.David Budtz Pedersen & Vincent F. Hendricks - 2014 - Philosophy and Technology 27 (4):503-518.
    Much like the trade and traits of bubbles in financial markets, similar bubbles appear on the science market. When economic bubbles burst, the drop in prices causes the crash of unsustainable investments leading to an investor confidence crisis possibly followed by a financial panic. But when bubbles appear in science, truth and reliability are the first victims. This paper explores how fashions in research funding and research management may turn science into something like a bubble economy.
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  • Dynamic Logics of Evidence-Based Beliefs.Johan van Benthem & Eric Pacuit - 2011 - Studia Logica 99 (1):61-92.
    This paper adds evidence structure to standard models of belief, in the form of families of sets of worlds. We show how these more fine-grained models support natural actions of “evidence management”, ranging from update with external new information to internal rearrangement. We show how this perspective leads to new richer languages for existing neighborhood semantics for modal logic. Our main results are relative completeness theorems for the resulting dynamic logic of evidence.
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  • Merging Frameworks for Interaction.Johan Benthem, Jelle Gerbrandy, Tomohiro Hoshi & Eric Pacuit - 2009 - Journal of Philosophical Logic 38 (5):491-526.
    A variety of logical frameworks have been developed to study rational agents interacting over time. This paper takes a closer look at one particular interface, between two systems that both address the dynamics of knowledge and information flow. The first is Epistemic Temporal Logic (ETL) which uses linear or branching time models with added epistemic structure induced by agents’ different capabilities for observing events. The second framework is Dynamic Epistemic Logic (DEL) that describes interactive processes in terms of epistemic event (...)
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  • Dynamic Logics of Evidence-Based Beliefs.J. Benthem & E. Pacuit - 2011 - Studia Logica 99 (1-3):61-92.
    This paper adds evidence structure to standard models of belief, in the form of families of sets of worlds. We show how these more fine-grained models support natural actions of “evidence management”, ranging from update with external new information to internal rearrangement. We show how this perspective leads to new richer languages for existing neighborhood semantics for modal logic. Our main results are relative completeness theorems for the resulting dynamic logic of evidence.
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  • Knowledge and Belief: An Introduction to the Logic of the Two Notions.Alan R. White - 1965 - Philosophical Quarterly 15 (60):268.
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  • Model Transformers for Dynamical Systems of Dynamic Epistemic Logic.Rasmus Kraemmer Rendsvig - 2015 - In Wiebe Van Der Hoek, Wesley H. Holliday & W. Wang (eds.), ogic, Rationality, and Interaction. LORI 2015. Lecture Notes in Computer Science, vol 9394. Springer.
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  • Semantic results for ontic and epistemic change. van Ditmarsch, Hans & Kooi, Barteld - unknown
    Hans van Ditmarsch and Barteld Kooi (2008). Semantic results for ontic and epistemic change. In: G. Bonanno, W. van der Hoek and M. Wooldridge (editors). Logic and the Foundations of Game and Decision Theory (LOFT 7). Texts in Logic and Games 3, pp. 87-117, Amsterdam University Press, Amsterdam.
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  • Examining Network Effects in an Argumentative Agent-Based Model of Scientific Inquiry.AnneMarie Borg, Daniel Frey, Dunja Šešelja & Christian Straßer - 2017 - In Alexandru Baltag, Jeremy Seligman & Tomoyuki Yamada (eds.), Logic, Rationality, and Interaction (LORI 2017, Sapporo, Japan). Springer. pp. 391--406.
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