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, 2005 Harsányi introduced the concept of type space in an intuitive way. Later Heifetz and Samet formalized it. Harsányi used conditional probabilities to model the beliefs of the players, Heifetz and Samet avoided using conditional probabilities formally.
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Most games violate the common priors doctrine
International Journal of Economic Theory, 2010The type of a player in a game describes the beliefs of that player about the types of others. We show that the subset of vectors of such player‐type beliefs which obey the consistency condition sometimes called the Harsanyi doctrine is of Lebesgue measure zero.
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Common priors for generalized type spaces [PDF]
, 2011 The notion of common prior is well-understood and widely-used in the incomplete information games literature. For ordinary type spaces the common prior is defined. Pinter and Udvari (2011) introduce the notion of generalized type space. Generalized type spaces are models for various bonded rationality issues, for finite belief hierarchies, unawareness ...
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The Common Prior Assumption in Economic Theory
Economics and Philosophy, 1995Why is (it that) common priors are implicit or explicit in the vast majority of the differential information literature in economics and game theory? Why has the economic community been unwilling, in practice, to accept and actually use the idea of truly personal probabilities in much the same way that it did accept the idea of personal utility ...
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Correlation and Common Priors in Games with Incomplete Information
SSRN Electronic Journal, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Common Priors For Like-Minded Agents [PDF]
, 2003 Two agents are like-minded when their beliefs are equal once conditioned on knowledge of both of their types. Assuming the existence of an outside observer that is commonly known to be likeminded and uninformative about the insiders, we derive the existence of a common prior among the insiders, with the outsiders beliefs (appropriately conditioned ...
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Common Priors and Markov Chains
1996The type function of an agent, in a type space, associates with each state a probability distribution on the type space. Thus, a type function can be considered as a Markov chain on the state space. A common prior for the space turns out to be a probability distribution which is invariant under the type functions of all agents.
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Current treatment and recent progress in gastric cancer
Ca-A Cancer Journal for Clinicians, 2021Smita S Joshi, Brian D Badgwell
exaly