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Statements

Subject Item
dbr:Stochastically_stable_equilibrium
rdf:type
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rdfs:label
Stochastically stable equilibrium
rdfs:comment
In game theory, a stochastically stable equilibrium is a refinement of the evolutionarily stable state in evolutionary game theory, proposed by and Peyton Young. An evolutionary stable state S is also stochastically stable if under vanishing noise the probability that the population is in the vicinity of state S does not go to zero.
dbp:name
Stochastically stable equilibrium
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dbc:Game_theory_equilibrium_concepts dbc:Evolutionary_game_theory
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9391228
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742877233
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dbc:Evolutionary_game_theory dbr:Peyton_Young dbr:Evolutionary_game_theory dbr:Dean_Foster dbr:Evolutionarily_stable_state dbr:Mutation dbr:Game_theory dbr:Random dbr:Stag_hunt dbr:Solution_concept dbr:Potential dbc:Game_theory_equilibrium_concepts
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dbo:abstract
In game theory, a stochastically stable equilibrium is a refinement of the evolutionarily stable state in evolutionary game theory, proposed by and Peyton Young. An evolutionary stable state S is also stochastically stable if under vanishing noise the probability that the population is in the vicinity of state S does not go to zero. The concept is extensively used in models of learning in populations, where "noise" is used to model experimentation or replacement of unsuccessful players with new players (random mutation). Over time, as the need for experimentation dies down or the population becomes stable, the population will converge towards a subset of evolutionarily stable states. Foster and Young have shown that this subset is the set of states with the highest potential.
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