  The article presents research on the use of Monte-Carlo Tree Search (MCTS)
methods to create an artificial player for the popular card game "The Lord of
the Rings". The game is characterized by complicated rules, multi-stage round
construction, and a high level of randomness. The described study found that
the best probability of a win is received for a strategy combining expert
knowledge-based agents with MCTS agents at different decision stages. It is
also beneficial to replace random playouts with playouts using expert
knowledge. The results of the final experiments indicate that the relative
effectiveness of the developed solution grows as the difficulty of the game
increases.
