Equilibrium selection by co-evolution for bargaining problems under incomplete information about time preferences

Abstract- The main purpose of this work is to measure the effect of bargaining players’ information completeness on agreements in evolutionary environments. We apply Co-evolutionary Algorithms to solve four incomplete information bargaining problems. Empirical analyses indicate that without complete information of player(s)’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.

• Type: Conference
• Year: 2005
• Where: CEC
• Authors: Nanlin Jin
• Keywords: Artificial Intelligence, CEC 2005, Co-evolutionary Algorithm, Complex Dynamic Games, Incomplete Information Bargaining