Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 47 tok/s
Gemini 2.5 Pro 44 tok/s Pro
GPT-5 Medium 13 tok/s Pro
GPT-5 High 12 tok/s Pro
GPT-4o 64 tok/s Pro
Kimi K2 160 tok/s Pro
GPT OSS 120B 452 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

Optimisation of MCTS Player for The Lord of the Rings: The Card Game (2109.12001v1)

Published 24 Sep 2021 in cs.LG

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.

Citations (3)

Summary

We haven't generated a summary for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.