The ChessAIThon project (2025-1-ES01-KA220-VET-000354329) is co-funded by the European Union. The views and opinions expressed in this publication are those of the author(s) only and do not necessarily reflect those of the European Union or the Spanish Service for the Internationalisation of Education (SEPIE). Neither the European Union nor the National Agency SEPIE can be held responsible for them.
Table of Contents
Pedagogical Comparison
This integration is the key to AlphaZero's efficiency. It allows the system to compensate for the lower analysis speed (80 thousand positions/second of AlphaZero) with an extremely selective and high-quality search, unlike the broad and fast search of Stockfish ( 70 million/second ). MCTS also manages the balance between exploration (testing new moves) and exploitation (using strategies that have worked well), making it an effective Reinforcement Learning algorithm for decision-making.