Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning

Jean-Bastien Grill, Michal Valko, Remi Munos

Nov-21-2025, 07:17:08 GMT–Neural Information Processing Systems

Y ou are a robot and you live in a Markov decision process (MDP) with a finite or an infinite number of transitions from state-action to next states. Y ou got brains and so you plan before you act.

artificial intelligence, machine learning, node, (16 more...)

Neural Information Processing Systems

Nov-21-2025, 07:17:08 GMT

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  - Machine Learning > Learning Graphical Models
    - Undirected Networks > Markov Models (0.34)
  - Representation & Reasoning > Planning & Scheduling (1.00)

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Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning Jean-Bastien Grill Michal Valko Rémi Munos SequeL team, INRIA Lille - Nord Europe, France Google DeepMind, UK
Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning

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