
Distributed Nested Rollout Policy for Same Game
Negrevergne, Benjamin; Cazenave, Tristan (2017), Distributed Nested Rollout Policy for Same Game, in Cazenave, Tristan; Winands, Mark H.M.; Saffidine, Abdallah, Computer Games, Revised Selected Papers, Springer : Cham, p. 108-120. 10.1007/978-3-319-75931-9_8
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Type
Communication / ConférenceDate
2017Conference title
6th Workshop, CGW 2017, Held in Conjunction with the 26th International Conference on Artificial Intelligence, IJCAI 2017Conference date
2017-08Conference city
Melbourne, VICConference country
AustraliaBook title
Computer Games, Revised Selected PapersBook author
Cazenave, Tristan; Winands, Mark H.M.; Saffidine, AbdallahPublisher
Springer
Published in
Cham
ISBN
978-3-319-75930-2
Pages
108-120
Publication identifier
Metadata
Show full item recordAuthor(s)
Negrevergne, Benjamin
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Cazenave, Tristan
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
Nested Rollout Policy Adaptation (NRPA) is a Monte Carlo search heuristic for puzzles and other optimization problems. It achieves state-of-the-art performance on several games including SameGame. In this paper, we design several parallel and distributed NRPA-based search techniques, and we provide a number of experimental insights about their execution. Finally, we use our best implementation to discover 15 better scores for 20 standard SameGame boards.Subjects / Keywords
computer games; artificial intelligenceRelated items
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