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Game tree

A game tree is a branching representation whose nodes denote game states and whose edges denote possible moves between them.

How 2 Manning books explain it

Grokking AI Algorithms, Second Edition

A tree representation whose nodes are game states and whose branches represent possible moves between them.

How it is used
Represents possible game futures for Minimax search and decision-making.
How deep it goes
Explains nodes, branches, leaves, alternating turns, heuristic evaluation, and depth limits, but not full-tree feasibility beyond resource constraints.
Examples
Uses simulated alternating turns, heuristic-scored leaf states, and Connect Four positions as concrete examples.
What you can do after
Apply it via Minimax search to organize valid moves, simulate future states, and compare resulting scores.

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Inside AI

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

How it is used
Models the branching possibilities that arise when computers analyze turn-based games.
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.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.