Games with Incomplete Information Played by "Bayesian" Players, I-III: Part I. The Basic Model&

By John C. Harsanyi. Management Sciences, 2004

2,277 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/87ca9af97281edd6fb3ecd20ecc9caf6df905d03

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In Economics and Econometrics

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Citations in the corpus

On the Generic (Im)possibility of Full Surplus Extraction in Mechanism Design (2006, background): “Since full-surplus-extraction results make heavy use of the fixed finite type space assumption, it is natural to ask whether or not the possibility of full-surplus-extraction extends to the most general consistent private information type space imaginable, or to the collection of consistent (in the ”
Strategic bidding of transmission-constrained GENCOs with incomplete information (2005, methodology): “However, based on the Harsanyi transformation [ 25 ], optimization problems are equivalent to a single optimization problem, given the following conditions:”
Information-Theoretic Bounded Rationality (2015, background): “easoning as a formal solution to the bounded-rationality problem. Formal solution. The problem can be solved by modeling the agent’s deliberation as a game of incomplete information or Bayesian game [Harsanyi, 1967]. Such a game allows us to represent the agent’s ignorance about the very objective f”
Pragmatic reasoning through semantic inference (2016, background): “The relevant notion of equilibrium for signalling games is the Bayesian Nash equilibrium (Harsanyi 1967), which in addition to the requirements imposed by the definition of the Nash equilibrium also imposes consistency constraints on the beliefs of the agents.”
Learning to play Bayesian games (2004, background): “1 Harsanyi (1967) proposed that games of incomplete information be analyzed as games with a move by”
Trust and social capital in the regulation of lending activities (2003, background): “With respect to game theory ( Harsanyi, 1967; Kreps, 1990; Shubik, 1982), we argue that a financial advisor does not optimize an unique exchange with an unique borrower but optimizes several exchanges with all members of a social group in the context of incomplete information.”
Information sharing in supply chains: Incentives for information distortion (2007, methodology): “We use the Bayesian Nash equilibrium concept, commonly used in incomplete information games such as ours, to derive the equilibrium ( Harsanyi, 1967 ).”