159 citations · 218 across the 15 of their papers we have counts for
4 papers · 1 filter
The Potential of the Return Distribution for Exploration in RL
Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker
This paper studies the potential of the return distribution for exploration in deterministic reinforcement learning (RL) environments. We study network losses and propagation mecha…
Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making
Luisa M Zintgraf, Diederik M Roijers, Sjoerd Linders +2
In multi-objective decision planning and learning, much attention is paid to producing optimal solution sets that contain an optimal policy for every possible user preference profi…
Efficient exploration with Double Uncertain Value Networks
Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker
This paper studies directed exploration for reinforcement learning agents by tracking uncertainty about the value of each available action. We identify two sources of uncertainty t…
Emotion in Reinforcement Learning Agents and Robots: A Survey
Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker
This article provides the first survey of computational models of emotion in reinforcement learning (RL) agents. The survey focuses on agent/robot emotions, and mostly ignores huma…