Dynamic landscape models of coevolutionary games
Abstract
Players of coevolutionary games may update not only their strategies but also their networks of interaction. Based on interpreting the payoff of players as fitness, dynamic landscape models are proposed. The modeling procedure is carried out for Prisoner's Dilemma (PD) and Snowdrift (SD) games that both use either birth--death (BD) or death--birth (DB) strategy updating. The main focus is on using dynamic fitness landscapes as a mathematical model of coevolutionary game dynamics. Hence, an alternative tool for analyzing coevolutionary games becomes available, and landscape measures such as modality, ruggedness and information content can be computed and analyzed. In addition, fixation properties of the games and quantifiers characterizing the interaction networks are calculated numerically. Relations are established between landscape properties expressed by landscape measures and quantifiers of coevolutionary game dynamics such as fixation probabilities, fixation times and network properties.
Cite
@article{arxiv.1611.09149,
title = {Dynamic landscape models of coevolutionary games},
author = {Hendrik Richter},
journal= {arXiv preprint arXiv:1611.09149},
year = {2017}
}
Comments
arXiv admin note: substantial text overlap with arXiv:1603.06374