activity
20222024
most citedDeep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties

11 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2024

Parallel Algorithms for Median Consensus Clustering in Complex Networks

Md Taufique Hussain, Mahantesh Halappanavar, Samrat Chatterjee +3

We develop an algorithm that finds the consensus of many different clustering solutions of a graph. We formulate the problem as a median set partitioning problem and propose a gree…

cs.LG2024★ 1 cited

Assessing the Impact of Distribution Shift on Reinforcement Learning Performance

Ted Fujimoto, Joshua Suetterlein, Samrat Chatterjee +1

Research in machine learning is making progress in fixing its own reproducibility crisis. Reinforcement learning (RL), in particular, faces its own set of unique challenges. Compar…

cs.LG2023★ 11 cited

Deep Reinforcement Learning for Cyber System Defense under Dynamic Adversarial Uncertainties

Ashutosh Dutta, Samrat Chatterjee, Arnab Bhattacharya +1

Development of autonomous cyber system defense strategies and action recommendations in the real-world is challenging, and includes characterizing system state uncertainties and at…

cs.RO2022★ 1 cited

AdverSAR: Adversarial Search and Rescue via Multi-Agent Reinforcement Learning

Aowabin Rahman, Arnab Bhattacharya, Thiagarajan Ramachandran +4

Search and Rescue (SAR) missions in remote environments often employ autonomous multi-robot systems that learn, plan, and execute a combination of local single-robot control action…

cs.MA2022

Ad Hoc Teamwork in the Presence of Adversaries

Ted Fujimoto, Samrat Chatterjee, Auroop Ganguly

Advances in ad hoc teamwork have the potential to create agents that collaborate robustly in real-world applications. Agents deployed in the real world, however, are vulnerable to…