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.

Deep learning and data analysis concepts for chess movement solving

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Part 1

The history of AI in chess is defined by the tension between brute force and selective learning. Initial programs, such as Deep Blue or world champion Stockfish, rely on alpha-beta search, an advanced form of brute force that uses human-adjusted heuristics to prune the search tree. Stockfish can analyze approximately 70 million positions per second.