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

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.