English

Control-Tutored Reinforcement Learning: an application to the Herding Problem

Machine Learning 2019-11-28 v2 Artificial Intelligence

Abstract

In this extended abstract we introduce a novel control-tutored Q-learning approach (CTQL) as part of the ongoing effort in developing model-based and safe RL for continuous state spaces. We validate our approach by applying it to a challenging multi-agent herding control problem.

Keywords

Cite

@article{arxiv.1911.11444,
  title  = {Control-Tutored Reinforcement Learning: an application to the Herding Problem},
  author = {Francesco De Lellis and Fabrizia Auletta and Giovanni Russo and Mario di Bernardo},
  journal= {arXiv preprint arXiv:1911.11444},
  year   = {2019}
}
R2 v1 2026-06-23T12:27:28.005Z