
A General Multi-Agent Modal Logic K Framework for Game Tree Search
Saffidine, Abdallah; Cazenave, Tristan (2012), A General Multi-Agent Modal Logic K Framework for Game Tree Search, dans Cazenave, Tristan; Méhat, Jean; Winands, Mark, Computer Games Workshop at ECAI 2012, European Conference on Artificial Intelligence, p. 18
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Type
Communication / ConférenceDate
2012Titre du colloque
Computer Games Workshop at ECAI 2012Date du colloque
2012-08Ville du colloque
MontpellierPays du colloque
FranceTitre de l'ouvrage
Computer Games Workshop at ECAI 2012Auteurs de l’ouvrage
Cazenave, Tristan; Méhat, Jean; Winands, MarkÉditeur
European Conference on Artificial Intelligence
Nombre de pages
142Pages
18
Métadonnées
Afficher la notice complèteAuteur(s)
Saffidine, AbdallahLaboratoire 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]
Résumé (EN)
We present an application of Multi-Agent Modal Logic K (MMLK) to model dynamic strategy game properties. We also provide several search algorithms to decide the model checking problem in MMLK. In this framework, we distinguish between the solution concept of in-terest which is represented by a class of formulas in MMLK and the search algorithm proper. The solution concept defines the shape of the game tree to be explored and the search algorithm determines how the game tree is explored. As a result, several formulas class and several of search algorithms can represent more than a dozen classical game tree search algorithms for single agent search, two-player games, and multi-player games. Among others, we can express the following algorithms in this work: depth-first search, Minimax, Monte Carlo Tree Search, Proof Number Search, Lambda Search, Paranoid Search, Best Reply Search.Mots-clés
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