Independent Learning in Constrained Markov Potential Games

1 code implementation • 27 Feb 2024 • Philip Jordan, Anas Barakat, Niao He

We propose an independent policy gradient algorithm for learning approximate constrained Nash equilibria: Each agent observes their own actions and rewards, along with a shared state.

Multi-agent Reinforcement Learning

Decentralized Federated Policy Gradient with Byzantine Fault-Tolerance and Provably Fast Convergence

1 code implementation • 7 Jan 2024 • Philip Jordan, Florian Grötschla, Flint Xiaofeng Fan, Roger Wattenhofer

We provide the first decentralized Byzantine fault-tolerant FRL method.