3 citations · 6 across the 12 of their papers we have counts for
3 papers · 1 filter
Regret Minimization and Convergence to Equilibria in General-sum Markov Games
Liad Erez, Tal Lancewicki, Uri Sherman +2
An abundance of recent impossibility results establish that regret minimization in Markov games with adversarial opponents is both statistically and computationally intractable. Ne…
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback
Tiancheng Jin, Tal Lancewicki, Haipeng Luo +2
The standard assumption in reinforcement learning (RL) is that agents observe feedback for their actions immediately. However, in practice feedback is often observed in delay. This…
Cooperative Online Learning in Stochastic and Adversarial MDPs
Tal Lancewicki, Aviv Rosenberg, Yishay Mansour
We study cooperative online learning in stochastic and adversarial Markov decision process (MDP). That is, in each episode, agents interact with an MDP simultaneously and share…