Bundle Classic AI algorithms: graph search, adversarial game search, optimization and tabular reinforcement learning (-lib ai)
MonteCarloTreeSearch
Monte Carlo tree search (UCT) over a GameState. Each playout selects by the UCB1 rule, expands one node, plays uniformly random moves to the end (or the rollout cap) and backs the evaluation up the tree. Seeded for reproducible searches; the most-visited root child is returned.
Example
mcts := MonteCarloTreeSearch->New(2000, 1.414, 7);
best := mcts->FindBestMove(state);