Strategic Maneuver and Disruption with Reinforcement Learning Approaches for Multi-Agent Coordination

no code implementations • 17 Mar 2022 • Derrik E. Asher, Anjon Basak, Rolando Fernandez, Piyush K. Sharma, Erin G. Zaroukian, Christopher D. Hsu, Michael R. Dorothy, Thomas Mahre, Gerardo Galindo, Luke Frerichs, John Rogers, John Fossaceca

Reinforcement learning (RL) approaches can illuminate emergent behaviors that facilitate coordination across teams of agents as part of a multi-agent system (MAS), which can provide windows of opportunity in various military tasks.

reinforcement-learning Reinforcement Learning (RL)

Survey of Recent Multi-Agent Reinforcement Learning Algorithms Utilizing Centralized Training

no code implementations • 29 Jul 2021 • Piyush K. Sharma, Rolando Fernandez, Erin Zaroukian, Michael Dorothy, Anjon Basak, Derrik E. Asher

Much work has been dedicated to the exploration of Multi-Agent Reinforcement Learning (MARL) paradigms implementing a centralized learning with decentralized execution (CLDE) approach to achieve human-like collaboration in cooperative tasks.

Multi-agent Reinforcement Learning reinforcement-learning +1