8 citations · 21 across the 11 of their papers we have counts for
3 papers · 1 filter
Health-Informed Policy Gradients for Multi-Agent Reinforcement Learning
Ross E. Allen, Jayesh K. Gupta, Jaime Pena +3
This paper proposes a definition of system health in the context of multiple agents optimizing a joint reward function. We use this definition as a credit assignment term in a poli…
Simulating Emergent Properties of Human Driving Behavior Using Multi-Agent Reward Augmented Imitation Learning
Raunak P. Bhattacharyya, Derek J. Phillips, Changliu Liu +3
Recent developments in multi-agent imitation learning have shown promising results for modeling the behavior of human drivers. However, it is challenging to capture emergent traffi…
Model Primitive Hierarchical Lifelong Reinforcement Learning
Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer
Learning interpretable and transferable subpolicies and performing task decomposition from a single, complex task is difficult. Some traditional hierarchical reinforcement learning…