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cs.LG2024
Principal-Agent Bandit Games with Self-Interested and Exploratory Learning Agents
Junyan Liu, Lillian J. Ratliff
We study the repeated principal-agent bandit game, where the principal indirectly interacts with the unknown environment by proposing incentives for the agent to play arms. Most ex…
cs.LG2024
Uniform Last-Iterate Guarantee for Bandits and Reinforcement Learning
Junyan Liu, Yunfan Li, Ruosong Wang +1
Existing metrics for reinforcement learning (RL) such as regret, PAC bounds, or uniform-PAC (Dann et al., 2017), typically evaluate the cumulative performance, while allowing the a…