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Game tree

As explained in Inside AI

A game tree is a branching representation whose nodes denote game states and whose edges denote states reachable through legal moves.

A game tree represents game states as nodes and legal moves as edges. Each player’s move creates branches of possible responses, forming a structure that can become extremely large. section 7.1

Chess search space

Chess typically offers about 30 legal moves per position and lasts roughly 40 move pairs. After three move pairs, more than 121 million board configurations may be possible. The Shannon number estimates the minimum number of possible chess games and illustrates why exhaustive enumeration is difficult. section 7.1

Traditional turn-based game programming, including IBM’s Deep Blue approach, stores the game tree in computer memory and evaluates the desirability of positions at branch endpoints. section 7.1

Figure 7.1 The starting position in chess (French Louvre collections of art) [1]
figure

Use the chess starting position to ground the abstract tree in a familiar board state before considering its legal continuations. section 7.1

How Inside AI covers it

How deep it goes
Defines nodes, edges, branching, and scale, then briefly connects the structure to endpoint evaluation in game programming.
Examples
Uses chess positions, move counts, the Shannon number, and IBM’s Deep Blue as concrete illustrations.
What you can do after
Evaluate the scale and structure of possible moves when reasoning about computer game-playing systems.
How it connects
Connects chess with legal moves, branching factor, Shannon number, and game-state evaluation.

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This explainer was generated by Manning's knowledge graph from the text of Inside AI. The section links point to the parts of the book it draws on.