53 citations · 105 across the 13 of their papers we have counts for
4 papers · 1 filter
A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
Dong-Ki Kim, Miao Liu, Matthew Riemer +6
A fundamental challenge in multiagent reinforcement learning is to learn beneficial behaviors in a shared environment with other simultaneously learning agents. In particular, each…
FISAR: Forward Invariant Safe Reinforcement Learning with a Deep Neural Network-Based Optimize
Chuangchuang Sun, Dong-Ki Kim, Jonathan P. How
This paper investigates reinforcement learning with constraints, which are indispensable in safety-critical environments. To drive the constraint violation monotonically decrease,…
Optimal Composition of Heterogeneous Multi-Agent Teams for Coverage Problems with Performance Bound Guarantees
Chuangchuang Sun, Shirantha Welikala, Christos G. Cassandras
We consider the problem of determining the optimal composition of a heterogeneous multi-agent team for coverage problems by including costs associated with different agents and sub…
Scaling Up Multiagent Reinforcement Learning for Robotic Systems: Learn an Adaptive Sparse Communication Graph
Chuangchuang Sun, Macheng Shen, Jonathan P. How
The complexity of multiagent reinforcement learning (MARL) in multiagent systems increases exponentially with respect to the agent number. This scalability issue prevents MARL from…