Monte Carlo tree search (MCTS) is a recently proposed search method that combines the
precision of tree search with the generality of random sampling. It has received considerable …

A new paradigm for search, based on Monte-Carlo simulation, has revolutionised the
performance of computer Go programs. In this article we describe two extensions to the …

This thesis studies the use of Monte-Carlo simulations for tree-search problems. The Monte-
Carlo technique we investigate is Monte-Carlo Tree Search (MCTS). It is a best-first search …

In this paper, Monte Carlo tree search (MCTS) is introduced for controlling the Pac-Man
character in the real-time game Ms Pac-Man. MCTS is used to find an optimal path for an …

Temporal-difference learning is one of the most successful and broadly applied solutions to
the reinforcement learning problem; it has been used to achieve master-level play in chess …

Whale optimization algorithm (WOA) is a population-based meta-heuristic imitating the
hunting behavior of humpback whales, which has been successfully applied to solve many …