254 citations · 662 across the 53 of their papers we have counts for
6 papers · 1 filter
Multi Agent Reinforcement Learning for Sequential Satellite Assignment Problems
Joshua Holder, Natasha Jaques, Mehran Mesbahi
Assignment problems are a classic combinatorial optimization problem in which a group of agents must be assigned to a group of tasks such that maximum utility is achieved while sat…
Learning to Cooperate with Humans using Generative Agents
Yancheng Liang, Daphne Chen, Abhishek Gupta +2
Training agents that can coordinate zero-shot with humans is a key mission in multi-agent reinforcement learning (MARL). Current algorithms focus on training simulated human partne…
InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma
Xiaoxuan Hou, Jiayi Yuan, Joel Z. Leibo +1
InvestESG is a novel multi-agent reinforcement learning (MARL) benchmark designed to study the impact of Environmental, Social, and Governance (ESG) disclosure mandates on corporat…
Infer Human's Intentions Before Following Natural Language Instructions
Yanming Wan, Yue Wu, Yiping Wang +2
For AI agents to be helpful to humans, they should be able to follow natural language instructions to complete everyday cooperative tasks in human environments. However, real human…
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning
Sriyash Poddar, Yanming Wan, Hamish Ivison +2
Reinforcement Learning from Human Feedback (RLHF) is a powerful paradigm for aligning foundation models to human values and preferences. However, current RLHF techniques cannot acc…
Achieving Human Level Competitive Robot Table Tennis
David B. D'Ambrosio, Saminda Abeyruwan, Laura Graesser +24
Achieving human-level speed and performance on real world tasks is a north star for the robotics research community. This work takes a step towards that goal and presents the first…