Online Learning for Uninformed Markov Games: Empirical Nash-Value Regret and Non-Stationarity Adaptation

Documenti analoghi

• On the Limitations and Possibilities of Nash Regret Minimization in Zero-Sum Matrix Games under Noisy Feedback
  di: Maiti, Arnab, et al.
  Pubblicazione: (2023)
• Improved Regret and Contextual Linear Extension for Pandora's Box and Prophet Inequality
  di: Liu, Junyan, et al.
  Pubblicazione: (2025)
• Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
  di: Liu, Junyan, et al.
  Pubblicazione: (2025)
• Proximal Regret and Proximal Correlated Equilibria: A New Tractable Solution Concept for Online Learning and Games
  di: Cai, Yang, et al.
  Pubblicazione: (2025)
• Convergence of Learning Dynamics in Stackelberg Games
  di: Fiez, Tanner, et al.
  Pubblicazione: (2019)