Game-Theory

An agent-based simulation framework that explores the Prisoner’s Dilemma on dynamic networks. Agents learn by imitating successful neighbors (Fermi Rule), adapt network connections, and face survival challenges based on economic success. Integrates memory-one strategies, wealth distribution, and network topology evolution to study cooperation emergence.

A Python project that explores the dynamics of cooperation and competition through the lens of game theory. Employing cellular automata and classic tactics like Tit For Tat, the project investigates the performance of various strategies in the context of the Prisoner’s Dilemma.