Corpus ID: 220265929

Model-based Reinforcement Learning: A Survey

@article{Moerland2020ModelbasedRL,
  title={Model-based Reinforcement Learning: A Survey},
  author={Thomas M. Moerland and Joost Broekens and Catholijn M. Jonker},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.16712}
}
  • Thomas M. Moerland, Joost Broekens, Catholijn M. Jonker
  • Published 2020
  • Computer Science, Mathematics
  • ArXiv
  • Sequential decision making, commonly formalized as Markov Decision Process (MDP) optimization, is a key challenge in artificial intelligence. Two key approaches to this problem are reinforcement learning (RL) and planning. This paper presents a survey of the integration of both fields, better known as model-based reinforcement learning. Model-based RL has two main steps. First, we systematically cover approaches to dynamics model learning, including challenges like dealing with stochasticity… CONTINUE READING

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