4 papers
S3: Stable Subgoal Selection by Constraining Uncertainty of Coarse Dynamics in Hierarchical Reinforcement Learning
Kshitij Kumar Srivastava, Kshitij Jerath
Hierarchical Reinforcement Learning (HRL) intends to separate strategic planning from primitive execution. It has been widely successful in solving long-horizon and complex tasks,…
Relational Weight Optimization for Enhancing Team Performance in Multi-Agent Multi-Armed Bandits
Monish Reddy Kotturu, Saniya Vahedian Movahed, Paul Robinette +3
We introduce an approach to improve team performance in a Multi-Agent Multi-Armed Bandit (MAMAB) framework using Fastest Mixing Markov Chain (FMMC) and Fastest Distributed Linear A…
Graph Attention Inference of Network Topology in Multi-Agent Systems
Akshay Kolli, Reza Azadeh, Kshitj Jerath
Accurately identifying the underlying graph structures of multi-agent systems remains a difficult challenge. Our work introduces a novel machine learning-based solution that levera…
Relational Q-Functionals: Multi-Agent Learning to Recover from Unforeseen Robot Malfunctions in Continuous Action Domains
Yasin Findik, Paul Robinette, Kshitij Jerath +1
Cooperative multi-agent learning methods are essential in developing effective cooperation strategies in multi-agent domains. In robotics, these methods extend beyond multi-robot s…