Transition-state replicator dynamics

作者：

Highlights：

• Additional reward parameter is added to the learning algorithm.

• The replicator equation is extended from single-state to transition-state.

• The algorithm and its dynamic are demonstrated on a 2 states battle of sexes game.

摘要

•Additional reward parameter is added to the learning algorithm.•The replicator equation is extended from single-state to transition-state.•The algorithm and its dynamic are demonstrated on a 2 states battle of sexes game.

论文关键词：Evolutionary game theory,Multi-agent learning,Replicator dynamics

论文评审过程：Received 13 August 2020, Revised 8 November 2020, Accepted 17 May 2021, Available online 24 May 2021, Version of Record 3 June 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115254