claw::ai::game::alpha_beta< State > Class Template Reference

Find an action with the alpha-beta algorithm. More...

#include <game_ai.hpp>

List of all members.

Public Types
typedef State	state
typedef State::action	action
typedef State::score	score

Public Member Functions
score	operator() (int depth, const state &current_state, bool computer_turn) const
	Apply the alpha-beta algorithm to find the best action.

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Detailed Description

template<typename State>
class claw::ai::game::alpha_beta< State >

Find an action with the alpha-beta algorithm.

Template parameters:

• State: the type of a state of the game. Must inherit from game_state.

Author:

Julien Jorge, Sébastien Angibaud

Definition at line 162 of file game_ai.hpp.

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Member Function Documentation

template<typename State >

State::score claw::ai::game::alpha_beta< State >::operator()	(	int	depth,
		const state &	current_state,
		bool	computer_turn
	)		const

Apply the alpha-beta algorithm to find the best action.

Parameters:

depth	Depth of the search subtree we are allowed to explore.
current_state	The state of the game.
computer_turn	Tell if the next action is done by the computer.

Definition at line 221 of file game_ai.tpp.

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The documentation for this class was generated from the following files:

• game_ai.hpp
• impl/game_ai.tpp