Agents
Multi-Agent Imitation Learning: Value is Easy, Regret is Hard
We consider the problem of a mediator learning to coordinate a group of strategic agents via recommendations of actions to take without knowledge of their underlying utility functions (e.g.
GenRL: Multimodal-foundation world models for generalization in embodied agents
Learning generalist embodied agents, able to solve multitudes of tasks in different domains is a long-standing problem.
Safety-Gymnasium: A Unified Safe Reinforcement Learning Benchmark
Artificial intelligence (AI) systems possess significant potential to drive societal progress. However, their deployment often faces obstacles due to substantial safety concerns.
Inverse Factorized Soft Q-Learning for Cooperative Multi-agent Imitation Learning
In a single-agent setting, IL was shown to be done efficiently via an inverse soft-Q learning process.