1 citations · 1 across the 3 of their papers we have counts for
4 papers
It's a matter of timescale: non-linear utility in successor features and multi-objective planning and learning
Liam P. H. Mertens, Lucas N. Alegre, Florent Delgrange +3
Time is of the essence when dealing with multiple reward signals and non-linear utility. In this paper we argue that the current main approaches in multi-objective RL (SER and ESR)…
Bridging the Gap Between Single and Multi Objective Games
Willem Röpke, Carla Groenland, Roxana Rădulescu +2
A classic model to study strategic decision making in multi-agent systems is the normal-form game. This model can be generalised to allow for an infinite number of pure strategies…
Sample-Efficient Multi-Objective Learning via Generalized Policy Improvement Prioritization
Lucas N. Alegre, Ana L. C. Bazzan, Diederik M. Roijers +2
Multi-objective reinforcement learning (MORL) algorithms tackle sequential decision problems where agents may have different preferences over (possibly conflicting) reward function…
Safe reinforcement learning for multi-energy management systems with known constraint functions
Glenn Ceusters, Luis Ramirez Camargo, Rüdiger Franke +2
Reinforcement learning (RL) is a promising optimal control technique for multi-energy management systems. It does not require a model a priori - reducing the upfront and ongoing pr…