From the 1 of 5 linked papers with an AI index.
5 papers
DNQ: Deep Nash Q-Network for Partially Observable n-Player Games
Qintong Xie, Edward Koh, Xavier Cadet +1
The paper introduces DNQ, a deep reinforcement learning framework that trains bidding agents for partially observable n‑player games by alternating between trajectory collection, c…
FORMULA: FORmation MPC with neUral barrier Learning for safety Assurance
Qintong Xie, Weishu Zhan, Peter Chin
Multi-robot systems (MRS) are essential for large-scale applications such as disaster response, material transport, and warehouse logistics, yet ensuring robust, safety-aware forma…
Optimistic Policy Regularization
Mai Pham, Vikrant Vaze, Peter Chin
Deep reinforcement learning agents frequently suffer from premature convergence, where early entropy collapse causes the policy to discard exploratory behaviors before discovering…
AsymPuzl: An Asymmetric Puzzle for multi-agent cooperation
Xavier Cadet, Edward Koh, Peter Chin
Large Language Model (LLM) agents are increasingly studied in multi-turn, multi-agent scenarios, yet most existing setups emphasize open-ended role-play rather than controlled eval…
Strategic Cyber Defense via Reinforcement Learning-Guided Combinatorial Auctions
Mai Pham, Vikrant Vaze, Peter Chin
Cyber defense operations increasingly require long-term strategic planning under uncertainty and resource constraints. We propose a new use of combinatorial auctions for allocating…