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Analiza drevesnega preiskovanja Monte Carlo v enostavnih šahovskih končnicah
ID BARACHINI, ROBERT (Author), ID Guid, Matej (Mentor) More about this mentor... This link opens in a new window

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Abstract
V diplomskem delu smo analizirali obnašanje algoritma drevesno preiskovanje Monte Carlo (ang. Monte Carlo tree search -- MCTS) v domeni enostavnih šahovskih končnic. Implementirali smo več hevristik za usmerjanje Monte Carlo simulacij in skozi postopek eksperimentiranja razvili več različic programa ter analizirali uspešnost posameznih hevristik in različnih konfiguracij algoritma. Odigrane poteze smo primerjali s popolno igro, pri čemer smo uporabili tabele šahovskih končnic Gaviota. V sklopu programskih rešitev je bil izdelan grafični vmesnik, ki omogoča spremljanje igre proti inteligentnemu agentu. Razvili smo več programov za analizo igre, poganjanje simulacij z različnimi nastavitvami ter vizualizacijo iskalnih dreves in ostalih rezultatov. Izvedli smo empirično študijo, v kateri smo ugotavljali vplive parametrov algoritma MCTS in kombinacij domenskih hevristik na kakovost igre programa.

Language:Slovenian
Keywords:drevesno preiskovanje Monte Carlo, MCTS, šah, šahovske končnice, hevristike, Stockfish, tabele končnic, Gaviota
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FRI - Faculty of Computer and Information Science
Year:2020
PID:20.500.12556/RUL-114084 This link opens in a new window
COBISS.SI-ID:1538535107 This link opens in a new window
Publication date in RUL:13.02.2020
Views:1930
Downloads:311
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Secondary language

Language:English
Title:Analysis of Monte Carlo tree search in simple chess endgames
Abstract:
In the thesis, we analyzed the behavior of the Monte Carlo tree search algorithm (MCTS) in the domain of simple chess endgames. We have implemented several heuristics for routing Monte Carlo simulations. Through the experimental process we have developed several versions of the program and analyzed the performance of individual heuristics and different configurations of the algorithm. The played moves were compared with perfect information using the Gaviota chess tablebases. As part of the software solutions, a graphical interface was created that allows monitoring the game against an intelligent agent. We have developed several programs to analyze the game, run simulations with different settings and visualize search trees and other results. We conducted an empirical study to determine the effect of the parameters of the MCTS algorithm and combinations of domain heuristics on the quality of play of the program.

Keywords:Monte Carlo tree search, MCTS, chess, chess endgames, heuristics, Stockfish, chess tablebases, Gaviota

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