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Knowledge Complement for Monte Carlo Tree Search: An Application to Combinatorial Games
TLDR
MCTS (Monte Carlo Tree Search) is a well-known and efficient process to cover and evaluate a large range of states for combinatorial problems. Expand
A Self-Acquiring Knowledge Process for MCTS
TLDR
MCTS (Monte Carlo Tree Search) is a well-known and efficient process to cover a large range of states for combinatorial problems. Expand
A new self-acquired knowledge process for Monte Carlo Tree Search
TLDR
We propose a new approach to extract game-based knowledge from the Go tree search which allows to increase the evaluation function accuracy (BHRF: Background History Reply Forest). Expand
Corrensites : genetic relationships assessed by multivariate statistical analysis
La corrensite est un mineral phylliteux interstratifie regulier 1 :1 de chlorite trioctaedrique avec une smectite trioctaedrique ou une vermiculite trioctaedrique ; la premiere est la corrensite deExpand
Dynamique d'apprentissage pour Monte Carlo Tree Search : applications aux jeux de Go et du Clobber solitaire impartial. (Learning dynamics for Monte Carlo Tree Search : application to combinatorial
TLDR
L'apprentissage du systeme resulte alors de la complexe interaction entre deux composantes : l'acquisition progressive de representations et la mobilisation de celles-ci lors des futures simulations.Depuis son introduction pour le jeu de Go, Monte Carlo Tree Search (MCTS) a ete applique avec succes a d'autres jeux. Expand
Ice sliding games
TLDR
This paper deals with sliding games, which are a variant of the better known pushpush game. Expand