1 citations · 2 across the 8 of their papers we have counts for
8 papers
AI Researchers Must Help Lead Arms Control to Mitigate Military AI Risks
Ted Fujimoto, Jacob Benz
The advancement of AI capabilities compels researchers and the public to be more aware of its potential worldwide impact. A pressing near-term concern is the regulation of military…
Large Language Model-Based Reward Design for Deep Reinforcement Learning-Driven Autonomous Cyber Defense
Sayak Mukherjee, Samrat Chatterjee, Emilie Purvine +2
Designing rewards for autonomous cyber attack and defense learning agents in a complex, dynamic environment is a challenging task for subject matter experts. We propose a large lan…
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…
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…
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…
Reward-Free Attacks in Multi-Agent Reinforcement Learning
Ted Fujimoto, Timothy Doster, Adam Attarian +2
We investigate how effective an attacker can be when it only learns from its victim's actions, without access to the victim's reward. In this work, we are motivated by the scenario…
How Can Creativity Occur in Multi-Agent Systems?
Ted Fujimoto
Complex systems show how surprising and beautiful phenomena can emerge from structures or agents following simple rules. With the recent success of deep reinforcement learning (RL)…
Adversarial Attacks in Cooperative AI
Ted Fujimoto, Arthur Paul Pedersen
Single-agent reinforcement learning algorithms in a multi-agent environment are inadequate for fostering cooperation. If intelligent agents are to interact and work together to sol…