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UCD : Upper confidence bound for rooted directed acyclic graphs

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UCD _ Upper Confidence bound for rooted Directed acyclic graphs.pdf (470.7Kb)
Date
2012
Dewey
Intelligence artificielle
Sujet
Monte-Carlo Tree Search; Transpositions; UCT Algorithm; Direct acyclic graph; Game tree search; Heuristic search
Journal issue
Knowledge-Based Systems
Volume
34
Publication date
2012
Article pages
26-33
Publisher
Elsevier
DOI
http://dx.doi.org/10.1016/j.knosys.2011.11.014
URI
https://basepub.dauphine.fr/handle/123456789/11569
Collections
  • LAMSADE : Publications
Metadata
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Author
Cazenave, Tristan
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Méhat, Jean
104738 Laboratoire d'Informatique Avancée de Saint-Denis [LIASD]
Saffidine, Abdallah
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Type
Article accepté pour publication ou publié
Abstract (EN)
In this paper we present a framework for testing various algorithms that deal with transpositions in Monte-Carlo Tree Search (MCTS). We call this framework Upper Confidence bound for Direct acyclic graphs (UCD) as it constitutes an extension of Upper Confidence bound for Trees (UCT) for Direct acyclic graphs (DAG).When using transpositions in MCTS, a DAG is progressively developed instead of a tree. There are multiple ways to handle the exploration exploitation dilemma when dealing with transpositions. We propose parameterized ways to compute the mean of the child, the playouts of the parent and the playouts of the child. We test the resulting algorithms on several games. For all games, original configurations of our algorithms improve on state of the art algorithms.

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