Equilibrium Selection by Co-evolution for Bargaining Problems under Incomplete Information about Time Preferences

Nanlin Jin

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The main purpose of this work is to measure the impact of players' information completeness on the outcomes in dynamic strategic games. We apply co-evolutionary algorithms to solve four incomplete information bargaining problems and investigate the experimental outcomes on players' shares from agreements, the efficiency of agreements and the evolutionary time for convergence. Empirical analyses indicate that in the absence of complete information on the counterpart(s)' preferences, co-evolving populations are still able to select equilibriums which are Pareto-efficient and stationary. This property of the co-evolutionary algorithm supports its future applications on complex dynamic games.
Original languageEnglish
Title of host publication2005 IEEE Congress on Evolutionary Computation
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages2661-2668
Volume3
ISBN (Print)0-7803-9363-5
DOIs
Publication statusPublished - 2005

Fingerprint

Dive into the research topics of 'Equilibrium Selection by Co-evolution for Bargaining Problems under Incomplete Information about Time Preferences'. Together they form a unique fingerprint.

Cite this