Monte Carlo tree search: A review of recent modifications and applications
Abstract Monte Carlo Tree Search (MCTS) is a powerful approach to designing game-
playing bots or solving sequential decision problems. The method relies on intelligent tree …
playing bots or solving sequential decision problems. The method relies on intelligent tree …
On monte carlo tree search and reinforcement learning
Fuelled by successes in Computer Go, Monte Carlo tree search (MCTS) has achieved wide-
spread adoption within the games community. Its links to traditional reinforcement learning …
spread adoption within the games community. Its links to traditional reinforcement learning …
Monte Carlo tree search with heuristic evaluations using implicit minimax backups
Monte Carlo Tree Search (MCTS) has improved the performance of game engines in
domains such as Go, Hex, and general game playing. MCTS has been shown to outperform …
domains such as Go, Hex, and general game playing. MCTS has been shown to outperform …
Nested Monte Carlo search for two-player games
The use of the Monte Carlo playouts as an evaluation function has proved to be a viable,
general technique for searching intractable game spaces. This facilitate the use of statistical …
general technique for searching intractable game spaces. This facilitate the use of statistical …
MCTS-minimax hybrids
Monte Carlo tree search (MCTS) is a sampling-based search algorithm that is state of the art
in a variety of games. In many domains, its Monte Carlo rollouts of entire games give it a …
in a variety of games. In many domains, its Monte Carlo rollouts of entire games give it a …
MCTS-minimax hybrids with state evaluations
Monte-Carlo Tree Search (MCTS) has been found to show weaker play than minimax-based
search in some tactical game domains. This is partly due to its highly selective search and …
search in some tactical game domains. This is partly due to its highly selective search and …
Game tree search for minimizing detectability and maximizing visibility
We introduce and study the problem of planning a trajectory for an agent to carry out a
scouting mission while avoiding being detected by an adversarial opponent. This introduces …
scouting mission while avoiding being detected by an adversarial opponent. This introduces …
Evolving game-specific UCB alternatives for general video game playing
At the core of the most popular version of the Monte Carlo Tree Search (MCTS) algorithm is
the UCB1 (Upper Confidence Bound) equation. This equation decides which node to …
the UCB1 (Upper Confidence Bound) equation. This equation decides which node to …
[HTML][HTML] An analysis for strength improvement of an MCTS-based program playing Chinese dark chess
Monte Carlo tree search (MCTS) has been successfully applied to many games recently.
Since then, many techniques are used to improve the strength of MCTS-based programs …
Since then, many techniques are used to improve the strength of MCTS-based programs …
Comprehensive Survey of Reinforcement Learning: From Algorithms to Practical Challenges
Reinforcement Learning (RL) has emerged as a powerful paradigm in Artificial Intelligence
(AI), enabling agents to learn optimal behaviors through interactions with their environments …
(AI), enabling agents to learn optimal behaviors through interactions with their environments …