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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Arslan, G. Shamma, J.S. |
| Copyright Year | 2006 |
| Description | Author affiliation: Dept. of Electr. Eng., Univ. of Hawaii at Manoa, Honolulu, HI (Arslan, G.) |
| Abstract | We investigate the problem of convergence to Nash equilibrium for learning in games. Prior work demonstrates how various learning models need not converge to a Nash equilibrium strategy and may even result in chaotic behavior. More recent work demonstrates how the notion of "anticipatory" learning, or, using more traditional feedback control terminology ,"lead compensation", can be used to enable convergence through a simple modification of existing learning models. In this paper, we show that this approach is broadly applicable to a variety of evolutionary game models. We also discuss single population evolutionary models. We introduce "anticipatory" replicator dynamics and discuss the relationship to evolutionary stability |
| Starting Page | 6289 |
| Ending Page | 6294 |
| File Size | 266525 |
| Page Count | 6 |
| File Format | |
| ISBN | 1424401712 |
| DOI | 10.1109/CDC.2006.376684 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-12-13 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Nash equilibrium Convergence Feedback control Chaos Terminology Aerodynamics USA Councils Stability Aerospace engineering Feedback loop |
| Content Type | Text |
| Resource Type | Article |
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