6 papers
Stabilization Limits of Payoff-Based Higher-Order Replicator Dynamics
Hassan Abdelraouf, Vijay Gupta, Jeff S. Shamma
Replicator dynamics (RD) is a fundamental model in learning in games, connecting evolutionary game theory and online learning. This paper studies payoff-based higher-order variants…
Learning Empirical Evidence Equilibria under Weak Environmental Coupling
Aya Hamed, Jason R. Marden, Jeff S. Shamma
Strategic multi-agent systems are fundamentally characterized by decentralization, uncertainty, and ambiguity. Agents operating under limited observations will often need to make d…
Convergence of Payoff-Based Higher-Order Replicator Dynamics in Contractive Games
Hassan Abdelraouf, Vijay Gupta, Jeff S. Shamma
We study the convergence properties of a payoff-based higher-order version of replicator dynamics, a widely studied model in evolutionary dynamics and game-theoretic learning, in c…
Can a Learner Regret Using a No-Regret Algorithm? A Control-Theoretic Study of Performance Dominance
Hassan Abdelraouf, Jeff S. Shamma
No-regret learning dynamics ensure that a learner asymptotically achieves an average reward no worse than that of any fixed strategy. This no-regret guarantee does not determine th…
Zeroth-Order Constrained Optimization from a Control Perspective via Feedback Linearization
Runyu Zhang, Gioele Zardini, Asuman Ozdaglar +2
Safe derivative-free optimization under unknown constraints is a fundamental challenge in modern learning and control. Existing zeroth-order (ZO) methods typically still assume acc…
Optimism as Risk-Seeking in Multi-Agent Reinforcement Learning
Runyu Zhang, Na Li, Asuman Ozdaglar +2
Risk sensitivity has become a central theme in reinforcement learning (RL), where convex risk measures and robust formulations provide principled ways to model preferences beyond e…