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Optimisation of MCTS player for The Lord of the Rings: The Card Game

Konrad Godlewski Bartosz Sawicki
Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e136752 | DOI: 10.24425/bpasts.2021.136752
Keywords Computational Intelligence Monte-Carlo Tree Search LoTR
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Abstract

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.
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Authors and Affiliations

Konrad Godlewski
1
Bartosz Sawicki
1
  1. Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warsaw, Poland

Computational Intelligence in engineering practice

Stanislaw Osowski Bartosz Sawicki Andrzej Cichocki
Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 3 | e137052 | DOI: 10.24425/bpasts.2021.137052
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Authors and Affiliations

Stanislaw Osowski
1 2
ORCID: ORCID
Bartosz Sawicki
1
Andrzej Cichocki
3
  1. Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, Poland
  2. Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland
  3. RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0106, Japan

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