Towards MCTS for Creative Domains.
Cameron Browne · 2011
Monte Carlo Tree Search (MCTS) has recently demonstrated considerable success for computer Go and other difficult AI problems. We present a general MCTS model that extends its application from searching for optimal actions in games and combinatorial optimisation tasks to the search for optimal sequences and embedded subtrees. The primary application of this extended MCTS model will be for creative domains, as it maps naturally to a range of procedural content generation tasks for which Markovian or evolutionary approaches would typically be used.