no code implementations • 23 Dec 2023 • Md Saiful Islam, Srijita Das, Sai Krishna Gottipati, William Duguay, Clodéric Mars, Jalal Arabneydi, Antoine Fagette, Matthew Guzdial, Matthew-E-Taylor
In this work, we show that learning from humans is effective and that human-AI collaboration outperforms human-controlled and fully autonomous AI agents in a complex simulation environment.
no code implementations • 19 Dec 2023 • Rupali Bhati, Sai Krishna Gottipati, Clodéric Mars, Matthew E. Taylor
While there has been significant progress in curriculum learning and continuous learning for training agents to generalize across a wide variety of environments in the context of single-agent reinforcement learning, it is unclear if these algorithms would still be valid in a multi-agent setting.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 18 Dec 2023 • Laila El Moujtahid, Sai Krishna Gottipati, Clodéric Mars, Matthew E. Taylor
With this platform, we hope to facilitate further research on human-machine teaming in critical systems and defense environments.
no code implementations • 21 Jun 2021 • AI Redefined, Sai Krishna Gottipati, Sagar Kurandwad, Clodéric Mars, Gregory Szriftgiser, François Chabot
Involving humans directly for the benefit of AI agents' training is getting traction thanks to several advances in reinforcement learning and human-in-the-loop learning.