A Modeling and Experimental Study on Game Learning Theory Based on Fairness

By incorporating fairness factor in the EWA (experience-weighted attraction) learning model, an extended game learning model was developed which is called FLG model. It uses the psychological effect instead of material effect to modify strategy's payoff and attraction, then, to study the equilibrium movement in dynamic Games. Psychological function changes when participants have fair thinking. Compared with EWA learning model by simulating the decision-making in Ultimatum Game, the result reveals that FLG model converges to the equilibrium strategy faster. An experiment about ice-cream cake distribution bargaining was designed and carried out. The experiment data proves that participants behave with fair thinking, learning and so on. At last, used the experiment data to test FLG model and EWA learning model, the results indicate that both models can converges to the equilibrium strategy, but FLG model moves to equilibrium faster and has more forecasting ability on participants' strategy behavior than EWA teaming model.