4 papers
Track-MDP: Reinforcement Learning for Target Tracking with Controlled Sensing
Adarsh M. Subramaniam, Argyrios Gerogiannis, James Z. Hare +1
State of the art methods for target tracking with sensor management (or controlled sensing) are model-based and are obtained through solutions to Partially Observable Markov Decisi…
Adversarial Attacks on Reinforcement Learning Agents for Command and Control
Ahaan Dabholkar, James Z. Hare, Mark Mittrick +4
Given the recent impact of Deep Reinforcement Learning in training agents to win complex games like StarCraft and DoTA(Defense Of The Ancients) - there has been a surge in research…
StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments
Sean Kulinski, Nicholas R. Waytowich, James Z. Hare +1
Spatial reasoning tasks in multi-agent environments such as event prediction, agent type identification, or missing data imputation are important for multiple applications (e.g., a…
Enhancing Multi-Agent Coordination through Common Operating Picture Integration
Peihong Yu, Bhoram Lee, Aswin Raghavan +3
In multi-agent systems, agents possess only local observations of the environment. Communication between teammates becomes crucial for enhancing coordination. Past research has pri…