393 citations · 835 across the 28 of their papers we have counts for
3 papers · 1 filter
Emergency action termination for immediate reaction in hierarchical reinforcement learning
Michał Bortkiewicz, Jakub Łyskawa, Paweł Wawrzyński +3
Hierarchical decomposition of control is unavoidable in large dynamical systems. In reinforcement learning (RL), it is usually solved with subgoals defined at higher policy levels…
The Effectiveness of World Models for Continual Reinforcement Learning
Samuel Kessler, Mateusz Ostaszewski, Michał Bortkiewicz +5
World models power some of the most efficient reinforcement learning algorithms. In this work, we showcase that they can be harnessed for continual learning - a situation when the…
Reinforcement learning with experience replay and adaptation of action dispersion
Paweł Wawrzyński, Wojciech Masarczyk, Mateusz Ostaszewski
Effective reinforcement learning requires a proper balance of exploration and exploitation defined by the dispersion of action distribution. However, this balance depends on the ta…