The Importance of Non-Markovianity in Maximum State Entropy Exploration

7 February 2022

Papers citing "The Importance of Non-Markovianity in Maximum State Entropy Exploration"

6 / 6 papers shown

Title
Online Episodic Convex Reinforcement Learning B. Moreno Khaled Eldowa Pierre Gaillard Margaux Brégère Nadia Oudjane OffRL 27 0 0 12 May 2025
Enhancing Diversity in Parallel Agents: A Maximum State Entropy Exploration Story Vincenzo De Paola Riccardo Zamboni Mirco Mutti Marcello Restelli 19 0 0 02 May 2025
Global Reinforcement Learning: Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods Ric De Santi Manish Prajapat Andreas Krause 36 3 0 13 Jul 2024
Policy Gradient Algorithms Implicitly Optimize by Continuation Adrien Bolland Gilles Louppe D. Ernst 31 3 0 11 May 2023
Challenging Common Assumptions in Convex Reinforcement Learning Mirco Mutti Ric De Santi Piersilvio De Bartolomeis Marcello Restelli OffRL 24 21 0 03 Feb 2022
Reward-Free Exploration for Reinforcement Learning Chi Jin A. Krishnamurthy Max Simchowitz Tiancheng Yu OffRL 104 194 0 07 Feb 2020