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The Sequence Scope: Chess Learning Explainability
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📝 Editorial: Chess Learning Explainability
Chess has long been considered a solved problem in machine learning (ML) as many chess programs have achieved superhuman performance. However, chess still continues contributing to the ML field in surprising ways. One of those new areas of contributions has to do with understanding how deep learning models build knowledge representations in complex scenarios such as chess. Traditional chess engines often start with extensive collections of games as well as established knowledge pools of openings and mid-game and end-game tactics. That approach was challenged with recent chess models like DeepMind’s AlphaZero that mastered chess by simply playing games. AlphaZero quickly became the strongest chess engine in the world and also discovered all…
