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The prevalence of chaotic dynamics in games with many players

Abstract:

We study adaptive learning in a typical p-player game. The payoffs of the games are randomly generated and then held fixed. The strategies of the players evolve through time as the players learn. The trajectories in the strategy space display a range of qualitatively different behaviours, with attractors that include unique fixed points, multiple fixed points, limit cycles and chaos. In the limit where the game is complicated, in the sense that the players can take many possible actions, we use a generating-functional approach to establish the parameter range in which learning dynamics converge to a stable fixed point. The size of this region goes to zero as the number of players goes to infinity, suggesting that complex non-equilibrium behaviour, exemplified by chaos, is the norm for complicated games with many players.

Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41598-018-22013-5

Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Mathematical Institute
Role:
Author
ORCID:
0000-0001-7871-073X


Publisher:
Nature Publishing Group
Journal:
Scientific Reports More from this journal
Volume:
8
Issue:
4902
Publication date:
2018-03-20
Acceptance date:
2018-01-23
DOI:
ISSN:
2045-2322


Keywords:
Pubs id:
pubs:834846
UUID:
uuid:f80b6446-4842-4b32-8cd0-dc601d11e460
Local pid:
pubs:834846
Source identifiers:
834846
Deposit date:
2018-04-10
ARK identifier:

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