Author

L. N. Alegre

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Open access Jul 2026

Sample-Efficient Multi-Task and Multi-Objective Reinforcement Learning by Combining Multiple Behaviors

New multi-policy methods that empower RL agents to carefully learn multiple behaviors, each specialized in a particular task; and combine previously-learned behaviors to efficiently identify solutions to novel tasks, which, importantly, may require the agent to assign different preferences to each of its new objectives...

L. N. Alegre, Ana L. C. Bazzan, Bruno C. da Silva · Anais do XXXIX Concurso de T... · 0 citations

#artificial intelligence Preprint Aug 2026

It's a matter of timescale: non-linear utility in successor features and multi-objective planning and learning

This paper argues that the current main approaches in multi-objective RL (SER and ESR), and successor features, are insufficient, and motivates that this can indeed be the case by an example, leading to a new perspective, and a significant and non-trivial gap in the literature.

L. P. J. Mertens, L. N. Alegre, Florent Delgrange et al. · 0 citations