no code implementations • 4 May 2023 • Boling Yang, Liyuan Zheng, Lillian J. Ratliff, Byron Boots, Joshua R. Smith
Autocurricular training is an important sub-area of multi-agent reinforcement learning~(MARL) that allows multiple agents to learn emergent skills in an unsupervised co-evolving scheme.
1 code implementation • 25 Sep 2021 • Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff
The hierarchical interaction between the actor and critic in actor-critic based reinforcement learning algorithms naturally lends itself to a game-theoretic interpretation.
no code implementations • L4DC 2020 • Liyuan Zheng, Lillian Ratliff
Constrained Markov Decision Processes are a class of stochastic decision problems in which the decision maker must select a policy that satisfies auxiliary cost constraints.
1 code implementation • 20 Mar 2020 • Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff, Baosen Zhang
This paper focuses on finding reinforcement learning policies for control systems with hard state and action constraints.
no code implementations • 26 Jan 2020 • Liyuan Zheng, Lillian J. Ratliff
Constrained Markov Decision Processes are a class of stochastic decision problems in which the decision maker must select a policy that satisfies auxiliary cost constraints.
no code implementations • 6 Jul 2018 • Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff
The design of personalized incentives or recommendations to improve user engagement is gaining prominence as digital platform providers continually emerge.