Information content of coevolutionary game landscapes
March 20, 2018 Β· Declared Dead Β· π IEEE Congress on Evolutionary Computation
"No code URL or promise found in abstract"
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Authors
Hendrik Richter
arXiv ID
1803.07307
Category
q-bio.PE
Cross-listed
cs.NE,
physics.soc-ph
Citations
3
Venue
IEEE Congress on Evolutionary Computation
Last Checked
3 months ago
Abstract
Coevolutionary game dynamics is the result of players that may change their strategies and their network of interaction. For such games, and based on interpreting strategies as configurations, strategy-to-payoff maps can be defined for every interaction network, which opens up to derive game landscapes. This paper presents an analysis of these game landscapes by their information content. By this analysis, we particularly study the effect of a rescaled payoff matrix generalizing social dilemmas and differences between well-mixed and structured populations.
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