Evolutionary Game of WSLS on a Scale-Free Network

The WSLS (Win-Stay, Lose-Shift) model is an evolutionary game framework operating on a scale-free network topology. In this model, each network node represents a player, while edges between nodes indicate interaction relationships. During each generation, players determine their strategies based on neighboring players' strategies, then receive payoffs according to game outcomes. The simulation iterates through 20 generations by default, though this parameter can be adjusted through configuration variables in the implementation.

The WSLS model finds applications across multiple domains including social networks, ecological systems, and economic modeling. By simulating agent interactions through network-based evolutionary dynamics, researchers can better understand emergent behaviors and complex interactions within dynamical systems. From a coding perspective, the implementation typically involves network generation using Barabási-Albert algorithms, strategy update functions with conditional payoff comparisons, and iterative loops with convergence checks. Future research directions may explore WSLS applications to broader problem domains with enhanced stability analysis and dynamic behavior characterization through extended simulation parameters.