39 citations · 80 across the 6 of their papers we have counts for
6 papers
Emergent Behaviors in Multi-Agent Target Acquisition
Piyush K. Sharma, Erin Zaroukian, Derrik E. Asher +1
Only limited studies and superficial evaluations are available on agents' behaviors and roles within a Multi-Agent System (MAS). We simulate a MAS using Reinforcement Learning (RL)…
Strategic Maneuver and Disruption with Reinforcement Learning Approaches for Multi-Agent Coordination
Derrik E. Asher, Anjon Basak, Rolando Fernandez +9
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 provid…
Survey of Recent Multi-Agent Reinforcement Learning Algorithms Utilizing Centralized Training
Piyush K. Sharma, Rolando Fernandez, Erin Zaroukian +3
Much work has been dedicated to the exploration of Multi-Agent Reinforcement Learning (MARL) paradigms implementing a centralized learning with decentralized execution (CLDE) appro…
Measuring collaborative emergent behavior in multi-agent reinforcement learning
Sean L. Barton, Nicholas R. Waytowich, Erin Zaroukian +1
Multi-agent reinforcement learning (RL) has important implications for the future of human-agent teaming. We show that improved performance with multi-agent RL is not a guarantee o…
Adapting the Predator-Prey Game Theoretic Environment to Army Tactical Edge Scenarios with Computational Multiagent Systems
Derrik E. Asher, Erin Zaroukian, Sean L. Barton
The historical origins of the game theoretic predator-prey pursuit problem can be traced back to Benda, et al., 1985 [1]. Their work adapted the predator-prey ecology problem into…
Malware in the Future? Forecasting of Analyst Detection of Cyber Events
Jonathan Z. Bakdash, Steve Hutchinson, Erin G. Zaroukian +5
There have been extensive efforts in government, academia, and industry to anticipate, forecast, and mitigate cyber attacks. A common approach is time-series forecasting of cyber a…