Imitation dynamics and the replicator equation
arXiv:2404.00754 · doi:10.1209/0295-5075/ad473e
Abstract
Evolutionary game theory has impacted many fields of research by providing a mathematical framework for studying the evolution and maintenance of social and moral behaviors. This success is owed in large part to the demonstration that the central equation of this theory - the replicator equation - is the deterministic limit of a stochastic imitation (social learning) dynamics. Here we offer an alternative elementary proof of this result, which holds for the scenario where players compare their instantaneous (not average) payoffs to decide whether to maintain or change their strategies, and only more successful individuals can be imitated.
References in corpus (7)
- Statistical physics of human cooperation
- Evolutionary dynamics of group interactions on structured populations: A review
- Coevolutionary Dynamics: From Finite to Infinite Populations
- Cooperative Behavior in a Model of Evolutionary Snowdrift Games with -person Interactions
- Imitative learning as a connector of collective brains
- The dynamics of casual groups can keep free-riders at bay
- -player game formulation of the majority-vote model of opinion dynamics
Cited by in corpus (5)
- -player game formulation of the majority-vote model of opinion dynamics
- Solving the prisoner's dilemma trap in Hamilton's model of temporarily formed random groups
- When Less is More: Evolutionary Dynamics of Deception in a Sender-Receiver Game
- Revisiting institutional punishment in the -person prisoner's dilemma
- Finite Population Dynamics Resolve the Central Paradox of the Inspection Game