A memory-based spatial evolutionary game with the dynamic interaction between learners and profiteers
Bin Pi, Minyu Feng, Liang-Jian Deng

TL;DR
This paper introduces a memory-based spatial evolutionary game model with dynamic interactions between learners and profiteers, revealing how memory and interaction dynamics promote cooperation in networks.
Contribution
It develops a novel model incorporating memory and Markov-based interactions, advancing understanding of cooperation evolution in spatial games.
Findings
Dynamic interactions foster cooperation
Memory mechanisms promote cooperation among profiteers
Higher learning rates increase cooperators
Abstract
Spatial evolutionary games provide a valuable framework for elucidating the emergence and maintenance of cooperative behavior. However, most previous studies assume that individuals are profiteers and neglect to consider the effects of memory. To bridge this gap, in this paper, we propose a memory-based spatial evolutionary game with dynamic interaction between learners and profiteers. Specifically, there are two different categories of individuals in the network, including profiteers and learners with different strategy updating rules. Notably, there is a dynamic interaction between profiteers and learners, i.e., each individual has the transition probability between profiteers and learners, which is portrayed by a Markov process. Besides, the payoff of each individual is not only determined by a single round of the game but also depends on the memory mechanism of the individual.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
