Chessand Computation
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Web edition · 2026

Chess and computation

From the board to artificial intelligence

An open web edition about algorithms, search, learning, and the game that turned calculation into strategy.

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Editorial composition of a black knight, a white queen, and a green rook
AlgorithmsSearchLearningStrategy

Ideas that transformed the game

A progressive reading, from board representation to modern neural networks.

  1. Introduction
  2. 01Chess Problems
    1. 1.1The n-queens problemTo stimulate your curiosity and engagement in this fascinating chapter, allow me to reveal an intriguing incentive.
    2. 1.2The knight's tourIn this section, we will delve into the exploration of one of the most intriguing problems originating from the fascinating world of chess.
    3. 1.3The king's marchesIn this chapter, the question of how many routes a chess king can take, starting from one specific square to another, using the minimum number of moves will be addressed.
  3. 02Artificial Intelligence
    1. 2.1What is artificial intelligence?To delve deeper into the field of artificial intelligence (AI), it is essential to clearly distinguish several related terms.
    2. 2.2Formal definition of chessThe analysis of how artificial intelligence (AI) and its subfields approach the study of chess requires first the establishment of a defined objective.
    3. 2.3Game treeGame trees represent a fundamental structure for the conceptualization of strategies in games such as chess. This strategic tool originated for the first time in the 19th century.
    4. 2.4HeuristicsA heuristic is a strategic method or general rule that we employ to simplify decision-making or the resolution of complex problems.
    5. 2.5The minimax algorithmThe operation of the minimax algorithm is intrinsically anchored to its denomination. This algorithm is used to identify the theoretically optimal move in any perfect information game.
    6. 2.6Alpha-beta pruningAlpha-beta pruning is an efficient technique that drastically reduces the number of states visited in the game tree of the minimax algorithm.
    7. 2.7Board representationAfter exploring the search mechanisms in artificial intelligence games, it is crucial to examine another essential component: the representation of the game board.
    8. 2.8Advanced techniques in the game treeIn this section, we will focus on the different techniques employed to optimize the search in alpha-beta pruning, an essential strategy for efficiency in AI games.
  4. 03Deep Reinforcement Learning
    1. 3.1RewardReward is a key element in reinforcement learning, as it provides artificial intelligence (AI) with feedback regarding its performance, signaling whether its performance is correct or, on the contrary.
    2. 3.2PolicyPolicy, in terms of machine learning, represents the decisions made by an agent based on a given state. These policies can be classified in two main ways: deterministic and non-deterministic.
    3. 3.3ModelThe main objective of our model is to deeply understand the underlying dynamics of a game. This implies knowing the transition probabilities to different states after the execution of a specific action.
    4. 3.4Reinforcement learning algorithmsThe field of reinforcement learning has experienced remarkable effervescence in recent years, leading to the creation of considerable diversity in algorithms.
    5. 3.5Neural networksIn recent years, neural networks and reinforcement learning have been the main drivers of the incredible advancement of artificial intelligence.
    6. 3.6AlphaZeroIn this section we will delve into the analysis of a revolutionary module that has transformed the chess landscape as we know it.
  5. 04State of the Art
    1. 4.1Stockfish strikes backThe Stockfish development team, far from sitting idly by after its defeat against AlphaZero, decided to adopt a strategy that recalls the old saying: "If you can't beat your enemy, join him".
    2. 4.2Imitating human decision-makingThroughout this text we have delved into a multitude of strategies aimed at achieving a singular objective: developing superlative skills in the game of chess.
  6. 05Standards
  7. AFlowcharts
  8. BChess
  9. CChess Notation
  10. DRecommendations
  11. —References
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