A game theoretic framework for reinforcement learning and imitation learning
Luca Viano (Ph.D. Student)
Reinforcement Learning and Imitation Learning achieved impressive empirical results in recent years. Still, little is known about the theoretical properties of commonly used algorithms. This PhD project aims to use insights from the field of game theory and optimization to develop algorithms with mathematical guarantees. The hope is to bring contributions on the practical RL side as well, proposing theory grounded algorithms easily applicable and implementable.
|Primary Host:||Volkan Cevher (EPFL)|
|Exchange Host:||Gergely Neu (Universitat Pompeu Fabra)|
|PhD Duration:||01 September 2021 - 01 September 2025|
|Exchange Duration:||01 March 2023 - 01 September 2023 - Ongoing|