Package edu.columbia.cs.coms4701.search.adversarial

R&N ch 6: Adversarial Search.

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          Description

Interface Summary
CutoffTest<S extends GameState> A function which examines a game state at a particular depth, and returns true if a HeuristicStateEvaluationFunction, rather than deeper alpha-beta search should be used to evaluate the state.
GameNode<K extends AgentAction,S extends GameState> A node in a game tree.
GamePlayingAgentProgram<K extends AgentAction,P extends AgentPercept,S extends GameState> Interface for AgentPrograms that play games.
GameProblem<K extends AgentAction,S extends GameState> A search problem appropriate for formally describing a game.
GameState State in a game problem.
HeuristicStateEvaluationFunction<K extends AgentAction,S extends GameState,P extends GameProblem<K,S>> A node evaluation function that returns an estimated utility from a given position.
MinimaxFunction<K extends AgentAction,S extends GameState,P extends GameProblem<K,S>> A function which evaluates a state in a game tree and returns an exact minimax value, i.e.
MinimaxFunctionWithHeuristic<K extends AgentAction,S extends GameState,P extends GameProblem<K,S>> A minimax function that applies a cutoff test to states; for these states, rather than continuing the minimax search, it applies a HeuristicStateEvaluationFunction.
StateEvaluationFunction<K extends AgentAction,S extends GameState,P extends GameProblem<K,S>> A function which evaluates a state in a game tree and returns an exact or estimate utility of the game from a given position.
 

Package edu.columbia.cs.coms4701.search.adversarial Description

R&N ch 6: Adversarial Search.

Deals primarily with deterministic, turn-taking, two-player, zero-sum games of perfect information.

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