ResearchTrend.AI
On the Evolution of the MCTS Upper Confidence Bounds for Trees by Means of Evolutionary Algorithms in the Game of Carcassonne

On the Evolution of the MCTS Upper Confidence Bounds for Trees by Means of Evolutionary Algorithms in the Game of Carcassonne

E. López
G. Simpson
ArXivPDFHTML

Papers citing "On the Evolution of the MCTS Upper Confidence Bounds for Trees by Means of Evolutionary Algorithms in the Game of Carcassonne"

3 / 3 papers shown
Title
Broaden your SCOPE! Efficient Multi-turn Conversation Planning for LLMs using Semantic Space
Zhiliang Chen
Xinyuan Niu
Chuan-Sheng Foo
Bryan Kian Hsiang Low
53
1
0
14 Mar 2025
An Analysis on the Effects of Evolving the Monte Carlo Tree Search Upper Confidence for Trees Selection Policy on Unimodal, Multimodal and Deceptive Landscapes
An Analysis on the Effects of Evolving the Monte Carlo Tree Search Upper Confidence for Trees Selection Policy on Unimodal, Multimodal and Deceptive Landscapes
Edgar Galván López
Fred Valdez Ameneyro
11
0
0
21 Nov 2023
Towards Understanding the Effects of Evolving the MCTS UCT Selection Policy
Towards Understanding the Effects of Evolving the MCTS UCT Selection Policy
Fred Valdez Ameneyro
E. López
15
2
0
07 Feb 2023