David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Episteme 6 (2):145-163 (2009)
In recent years, various computational models have been developed for studying the dynamics of belief formation in a population of epistemically interacting agents that try to determine the numerical value of a given parameter. Whereas in those models, agents’ belief states consist of single numerical beliefs, the present paper describes a model that equips agents with richer belief states containing many beliefs that, moreover, are logically interconnected. Correspondingly, the truth the agents are after is a theory (a set of sentences of a given language) rather than a numerical value. The agents epistemically interact with each other and also receive evidence in varying degrees of informativeness about the truth. We use computer simulations to study how fast and accurately such populations as wholes are able to approach the truth under differing combinations of settings of the key parameters of the model, such as the degree of informativeness of the evidence and the weight the agents give to the evidence
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
Igor Douven (2010). Simulating Peer Disagreements. Studies in History and Philosophy of Science Part A 41 (2):148-157.
Gérard Weisbuch, Guillaume Deffuant, Frédéric Amblard & Jean‐Pierre Nadal (2002). Meet, Discuss, and Segregate! Complexity 7 (3):55-63.
Citations of this work BETA
Igor Douven & Sylvia Wenmackers (forthcoming). Inference to the Best Explanation Versus Bayes’s Rule in a Social Setting. British Journal for the Philosophy of Science:axv025.
Igor Douven & Christoph Kelp (2011). Truth Approximation, Social Epistemology, and Opinion Dynamics. Erkenntnis 75 (2):271-283.
Gustavo Cevolani (2014). Truth Approximation, Belief Merging, and Peer Disagreement. Synthese 191 (11):2383-2401.
Hugh Gash (forthcoming). Systems and Beliefs. Foundations of Science:1-11.
Similar books and articles
Brian Hill (2008). Towards a “Sophisticated” Model of Belief Dynamics. Part I: The General Framework. Studia Logica 89 (1):81 - 109.
Andrei A. Buckareff (2004). Acceptance and Deciding to Believe. Journal of Philosophical Research 29:173-190.
Mark Jago (2006). Resource-Bounded Belief Revision and Contraction. In P. Torroni, U. Endriss, M. Baldoni & A. Omicini (eds.), Declarative Agent Languages and Technologies III. Springer 141--154.
Stefan Schubert & Erik J. Olsson (2012). On the Coherence of Higher-Order Beliefs. Southern Journal of Philosophy 50 (1):112-135.
John Cantwell (2006). A Formal Model of Multi-Agent Belief-Interaction. Journal of Logic, Language and Information 15 (4):397-422.
John Cantwell (2005). A Formal Model of Multi-Agent Belief-Interaction. Journal of Logic, Language and Information 14 (4):397-422.
Renata Wassermann (1999). Resource Bounded Belief Revision. Erkenntnis 50 (2-3):429-446.
Stuart C. Shapiro & William J. Rapaport (1991). Models and Minds. In Robert E. Cummins & John L. Pollock (eds.), Philosophy and AI. Cambridge: MIT Press 215--259.
Hans Van Ditmarsch & Willem Labuschagne (2007). My Beliefs About Your Beliefs: A Case Study in Theory of Mind and Epistemic Logic. Synthese 155 (2):191 - 209.
Added to index2010-07-11
Total downloads16 ( #167,478 of 1,726,249 )
Recent downloads (6 months)4 ( #183,615 of 1,726,249 )
How can I increase my downloads?