ترویج همکاری بر اساس هوش مصنوعی در بازی های عمومی کالا فضایی

In this paper, we introduce the swarm intelligence methods into the evolutionary dynamics, and have studied the impact of swarm intelligent algorithm on the evolution of cooperation among selfish individuals in the continuous version of spatial public goods games (PGG). We update an individual’s strategy according to the memory which records the most successful individual strategy in the past (referred to as its personal best strategy) as well as the knowledge of the best current strategy found by its nearest neighbors (referred to as the neighborhood best strategy). Through extensive simulations, we find that the introduction of swarm intelligence into PGG can promote cooperation strongly. Other pertinent quantities such as the time evolution of cooperator density, the spatial distribution of strategies and the updated velocities are also investigated.