Philip Jordan
+41 21 695 59 02
EPFL › STI › IGM › SYCAMORE
Website: https://www.epfl.ch/labs/sycamore
Philip Jordan received both his Bachelor's and Master's degrees in Computer Science from ETH Zurich. During his Bachelor's, he spent one semester at Princeton University. In his Master's thesis, he studied independent learning in Markov potential games, and his current research interest continues to lie in the areas of (multi-agent) reinforcement learning, optimization, and game theory. Previously, he also co-founded a start-up in the field of smart contracts.
Selected publications
Independent Learning in Constrained Markov Potential Games
Philip Jordan, Anas Barakat, Niao He
Published in AISTATS '24: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics in
Decentralized Federated Policy Gradient with Byzantine Fault-Tolerance and Provably Fast Convergence
Philip Jordan, Florian Grötschla, Flint Xiaofeng Fan, Roger Wattenhofer
Published in AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems in