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See:
Description
Interface Summary | |
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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. |
R&N ch 6: Adversarial Search.
Deals primarily with deterministic, turn-taking, two-player, zero-sum games of perfect information.
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