TY - JOUR N2 - 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. L1 - http://www.journals.pan.pl/Content/119436/PDF/09_02013_Bpast.No.69(3)_23.06.21_Druk.pdf L2 - http://www.journals.pan.pl/Content/119436 PY - 2021 IS - 3 EP - e136752 DO - 10.24425/bpasts.2021.136752 KW - Computational Intelligence KW - Monte-Carlo Tree Search KW - LoTR A1 - Godlewski, Konrad A1 - Sawicki, Bartosz VL - 69 DA - 10.03.2021 T1 - Optimisation of MCTS player for The Lord of the Rings: The Card Game SP - e136752 UR - http://www.journals.pan.pl/dlibra/publication/edition/119436 T2 - Bulletin of the Polish Academy of Sciences Technical Sciences ER -