International audienceWe present an adaptative method that enables a General Game Player using Monte-Carlo Tree Search to adapt its use of RAVE to the game it plays. This adaptation is done with a comparison of the UCT and RAVE prediction for moves, that are based on previous playout results. We show that it leads to results that are equivalent to those obtained with a hand tuned choice of RAVE usage and better than a fit-for-all fixed choice on simple ad'hoc synthetic games. This is well adapted to the domain of General Game Playing where the player can not be tuned for the characteristics of the game it will play before the beginning of a match
In this paper, we put forward Monte-Carlo Tree Search as a novel, unified framework to game AI, whic...
We explore the effects of using a system similar to an opening book to improve the capabilities of c...
Monte-carlo tree search (mcts) has shown particular success in general game playing (ggp) and genera...
General Game Playing (GGP) aims at creating computer programs able to play any arbitrary game at an ...
Many enhancements have been proposed for Monte-Carlo Tree Search (MCTS). Some of them have been appl...
Monte Carlo Tree Search (MCTS) is the state of the art algorithm for General Game Playing (GGP). We ...
A purpose of General Video Game Playing (GVGP) is to create agents capable of playing many different...
International audienceMonte Carlo Tree Search (MCTS) is the state of the art algorithm for many game...
Monte-Carlo Tree Search (MCTS) has been applied successfully in many domains, including games. Howev...
Playout policy adaptation (ppa) is a state-of-the-art strategy that has been proposed to control the...
Many enhancements for Monte Carlo tree search (MCTS) have been applied successfully in general game ...
Monte-Carlo Tree Search (MCTS) has been applied successfully in many domains. Previous research has ...
Abstract. Monte-Carlo tree search, especially the UCT algorithm and its en-hancements, have become e...
Monte-carlo tree search (mcts) is a best-first search method guided by the results of monte-carlo si...
International audienceThe Monte-Carlo Tree Search algorithm has been successfully applied in various...
In this paper, we put forward Monte-Carlo Tree Search as a novel, unified framework to game AI, whic...
We explore the effects of using a system similar to an opening book to improve the capabilities of c...
Monte-carlo tree search (mcts) has shown particular success in general game playing (ggp) and genera...
General Game Playing (GGP) aims at creating computer programs able to play any arbitrary game at an ...
Many enhancements have been proposed for Monte-Carlo Tree Search (MCTS). Some of them have been appl...
Monte Carlo Tree Search (MCTS) is the state of the art algorithm for General Game Playing (GGP). We ...
A purpose of General Video Game Playing (GVGP) is to create agents capable of playing many different...
International audienceMonte Carlo Tree Search (MCTS) is the state of the art algorithm for many game...
Monte-Carlo Tree Search (MCTS) has been applied successfully in many domains, including games. Howev...
Playout policy adaptation (ppa) is a state-of-the-art strategy that has been proposed to control the...
Many enhancements for Monte Carlo tree search (MCTS) have been applied successfully in general game ...
Monte-Carlo Tree Search (MCTS) has been applied successfully in many domains. Previous research has ...
Abstract. Monte-Carlo tree search, especially the UCT algorithm and its en-hancements, have become e...
Monte-carlo tree search (mcts) is a best-first search method guided by the results of monte-carlo si...
International audienceThe Monte-Carlo Tree Search algorithm has been successfully applied in various...
In this paper, we put forward Monte-Carlo Tree Search as a novel, unified framework to game AI, whic...
We explore the effects of using a system similar to an opening book to improve the capabilities of c...
Monte-carlo tree search (mcts) has shown particular success in general game playing (ggp) and genera...