28 citations · 49 across the 8 of their papers we have counts for
8 papers
Stackelberg Games for Learning Emergent Behaviors During Competitive Autocurricula
Boling Yang, Liyuan Zheng, Lillian J. Ratliff +2
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 sc…
Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms
Liyuan Zheng, Tanner Fiez, Zane Alumbaugh +2
The hierarchical interaction between the actor and critic in actor-critic based reinforcement learning algorithms naturally lends itself to a game-theoretic interpretation. We adop…
Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks
Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff +1
This paper focuses on finding reinforcement learning policies for control systems with hard state and action constraints. Despite its success in many domains, reinforcement learnin…
Constrained Upper Confidence Reinforcement Learning
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. This p…
Koopman Operator Applications in Signalized Traffic Systems
Esther Ling, Liyuan Zheng, Lillian J. Ratliff +1
This paper proposes Koopman operator theory and the related algorithm dynamical mode decomposition (DMD) for analysis and control of signalized traffic flow networks. DMD provides…
Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences
Tanner Fiez, Shreyas Sekar, Liyuan Zheng +1
The design of personalized incentives or recommendations to improve user engagement is gaining prominence as digital platform providers continually emerge. We propose a multi-armed…
Towards a Socially Optimal Multi-Modal Routing Platform
Chinmaya Samal, Liyuan Zheng, Fangzhou Sun +2
The increasing rate of urbanization has added pressure on the already constrained transportation networks in our communities. Ride-sharing platforms such as Uber and Lyft are becom…
Uncertainty in Multi-Commodity Routing Networks: When does it help?
Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff +1
We study the equilibrium behavior in a multi-commodity selfish routing game with many types of uncertain users where each user over- or under-estimates their congestion costs by a…