Equilibrium stability as a driver of cooperation among Q-learners
Updated
Updated · arxiv.org · Jul 15
Equilibrium stability as a driver of cooperation among Q-learners
1 articles · Updated · arxiv.org · Jul 15
Summary
Researchers have identified equilibrium stability as a key driver of cooperation among Q-learning algorithms in repeated Prisoner’s Dilemma scenarios.
Their study shows that, under constant exploration and learning rates, cooperative strategies can dominate the time-averaged behavior of these algorithms.
This finding suggests that the resilience of cooperative outcomes to ongoing fluctuations is critical for understanding algorithmic collusion and its potential impact on social welfare.