Quantal Response Equilibria for Normal Form Games

By Richard D. McKelvey, Thomas R. Palfrey. 1995

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Citations in the corpus

Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization (2021, neutral): “In game theory, this is aligned with the quantal response equilibrium (McKelvey & Palfrey, 1995), a smoothed version of NE obtained when payoffs are perturbed by a Gumbel noise.”
Who Thinks about the Competition? Managerial Ability and Strategic Entry in US Local Telephone Markets (2011, unknown): “…for heterogeneity in the ability of players to correctly conjecture competitor behavior in entry games, including quantal response equilibrium (e.g., McKelvey and Palfrey 1995), level-k thinking (e.g., Costa-Gomes and Crawford 2006), and cognitive hierarchy (e.g., Camerer, Ho, and Chong 2004).”
Dictator game giving: altruism or artefact? (2008, methodology): “There are two approaches that currently predominate in the literature, models based on Fechner’ s (1966 [1860]) measurement error theory, such as that incorporated into Quantal Response Equilibrium analysis (McKelvey and Palfrey 1995), and the ‘random preferences’ model (Loomes and Sugden 1995).”
A Continuous Dilemma âˆ (2009, background): “In recent years, researchers have explored the efficiency-enhancing roles of spatial matchings, reward and punishment technologies and social preferences.”
Obviously Strategy-Proof Mechanisms (2017, unknown): “Quantal response equilibrium (QRE) is defined for normal form games (McKelvey and Palfrey, 1995).”
A Cognitive Hierarchy Model of Games (2004, background): “In quantal response equilibrium [Rosenthal, 1989; McKelvey and Palfrey, 1995, 1998], players' beliefs and choices of other players are consistent, but are stochastic.”
Endowment Effects in Contests (2009, unknown): “entire strategy space ( McKelvey and Palfrey, 1995 ).”
Empirical Models of Entry and Market Structure (2007, background): “As in McKelvey and Palfrey (1995) , interest often centers on estimating the variance of the errors in utility as opposed to parameters of the utility functions, ui(·, ·). The estimated variance sometimes is used to describe how close the quantal response equilibrium is to a Nash equilibrium.”