research
∙
05/04/2023
Stackelberg Games for Learning Emergent Behaviors During Competitive Autocurricula
Autocurricular training is an important sub-area of multi-agent reinforc...
share
research
∙
09/25/2021
Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms
The hierarchical interaction between the actor and critic in actor-criti...
research
∙
03/20/2020
Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks
This paper focuses on finding reinforcement learning policies for contro...
research
∙
01/26/2020
Constrained Upper Confidence Reinforcement Learning
Constrained Markov Decision Processes are a class of stochastic decision...
research
∙
07/06/2018
Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences
The design of personalized incentives or recommendations to improve user...
research
∙
03/11/2018
Incentives in the Dark: Multi-armed Bandits for Evolving Users with Unknown Type
Design of incentives or recommendations to users is becoming more common...
research
∙
02/27/2018
Towards a Socially Optimal Multi-Modal Routing Platform
The increasing rate of urbanization has added pressure on the already co...
research
∙
09/25/2017