Learning, Mutation, and Long Run Equilibria in Games

By Michihiro Kandori, George J. Mailath, Rafael Rob. 1993

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Citations in the corpus

Discovering Diverse Multi-Agent Strategic Behavior via Reward Randomization (2021, background): “…these algorithms can converge to when multiple NEs exist, e.g., the stag-hunt game and its variants, for which many learning dynamics fail to converge to a prevalence of the pure strategy Stag (Kandori et al., 1993; Ellison, 1993; Fang et al., 2002; Skyrms & Pemantle, 2009; Golman & Page, 2010)..”
Indirect reciprocity can stabilize cooperation without the second-order free rider problem (2004, unknown): “Within-group processes based on random fluctuation”
Social Learning and Coordination Conventions in Intergenerational Games: An Experimental Study (2003, background): “In Darwinian models of evolution, random mutations can arise that, if persistent enough, can cause a disruption of the current equilibrium and drift toward a new one (see Fudenberg and Maskin 1990; Samuelson and Zhang 1992; Kandori et al. 1993; Young 1993; Samuelson 1997).”
Prosocial learning agents solve generalized Stag Hunts better than selfish ones (2017, background): “Work in evolutionary game theory shows that in large population evolutionary processes in 2 × 2 games with multiple equilibria it is risk dominance not payoff dominance that serves as the unique convergence point (Kandori, Mailath, and Rob 1993; Nowak 2006; Fudenberg and Levine 1998).”
Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics (2009, background): “[45] showed that the risk-dominant equilibrium is selected when using a stochastic evolutionary game dynamics, proposed by Foster and Young [46], that considers that every player interacts with every other one (implying slow selection).”
A dynamic model of social network formation. (2000, background): “In models without structural dynamics, Kandori, Mailath and Rob (38) have shown that only the risk dominant equilibrium of a two player coordination game is stochastically stable.”
History, Expectations, and Leadership in the Evolution of Social Norms (2014, unknown): “An agent chooses an action only once.11 The stage payoff to an agent playing A when another agent plays A′ is denoted u(A, A′).”
Fast Equilibrium Selection by Rational Players Living in a Changing World (2001, background): “[26] Morris, Stephen, Rob, Rafael, and Hyun Song Shin.”
Network formation and social coordination (2005, unknown): “In order to determine this support, we use the techniques introduced in Kandori et al. (1993) and Young (1993).”
The Diffusion of Innovations in Social Networks (2000, result): “An analogous result holds in many other evolutionary learning models (Kandori, Mailath, and Rob, 1993; Young, 1993; Blume, 1995b; van Damme and Weibull (1999). following example.”
Sampling best response dynamics and deterministic equilibrium selection (2015, background): “…sometimes rely on unusual (though inevitable) sequences of samples that lead 6It is worth noting that the the stochastic evolutionary dynamics of Kandori et al. (1993) and Young (1993) do not respect iterated p-dominance in this game, as it can be shown that action 2 is stochastically stable.”
ON THE GLOBAL CONVERGENCE OF STOCHASTIC FICTITIOUS PLAY (2002, methodology): “Finally, Kandori and Rob (1995) use the monotonicity of best responses to characterize the stochastically stable states of the Kandori, Mailath, and Rob (1993) model in certain supermodular games.”