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Št. zadetkov: 2
Learning to play the chess variant Crazyhouse with deep learning and domain knowledge
Anei Makovec, Matej Guid, Johanna Pirker
Magistrsko delo
Oznake: chess version Crazyhouse;chess versions;chess;learning to play;domain knowledge;best-change rates;Monte Carlo tree search;computer science;master's thesis;
In the evolving landscape of game-playing algorithms, Crazyhouse's reintroduction of captured pieces presents a unique challenge that distinguishes it from traditional chess. In this thesis, we explore a hybrid approach that combines domain knowledge with neural network-based evaluations, aiming for ...
Leto: 2023 Vir: Fakulteta za računalništvo in informatiko (UL FRI)
Adapting AlphaZero for three-player hexagonal chess
Jan Vasiljević, Marko Bajec, Johanna Pirker, Aleksander Sadikov
Magistrsko delo
Oznake: multiplayer chess;AlphaZero;transformer;deep reinforcement learning;non-zero-sum games;game theory;computer science;master's thesis;
This thesis adapts the AlphaZero framework for Three-Way Chess, a three-player variant defined by hexagonal geometry and complex coalition dynamics. To address the lack of software frameworks, a high-performance training ecosystem was developed for resource-constrained hardware. A transformer-based ...
Leto: 2025 Vir: Fakulteta za računalništvo in informatiko (UL FRI)
Št. zadetkov: 2
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