C# 클래스 social_learning.QLearningAgent

A Q-Learning teacher. The teacher learns via the Q-Learning Temporal Difference Algorithm.

상속: NeuralAgent

공개 프로퍼티들

프로퍼티	타입	설명
_prevState	double[]

메소드	설명
QLearningAgent ( int id, int speciesId, IBlackBox brain, bool agentsNavigate, bool agentsHide, int numOrientationActions, int numVelocityActions, World world ) : System	Creates a new Q-Learning teacher.
activateNetwork ( double sensors ) : ISignalArray	Called at every step in the world. Given the sensor input, returns the change in orientation and velocity in the range [0,1].

메소드	설명
greedyValue ( double sensors ) : double
selectEpsilonGreedy ( double sensors ) : double[]
selectGreedy ( double sensors ) : double[]
selectRandom ( double sensors ) : double[]
updateValueFunction ( double sensors ) : void
world_PlantEaten ( object sender, IAgent eater, Plant eaten ) : void

Creates a new Q-Learning teacher.

public QLearningAgent ( int id, int speciesId, IBlackBox brain, bool agentsNavigate, bool agentsHide, int numOrientationActions, int numVelocityActions, World world ) : System
id	int	The unique ID of this teacher.
speciesId	int
brain	IBlackBox	The neural network value function for this teacher. It should have (2 + # of sensors) input nodes and 1 output node.
agentsNavigate	bool
agentsHide	bool
numOrientationActions	int	The number of buckets to discretize the orientation action spacer into.
numVelocityActions	int	The number of buckets to discretize the velocity action spacer into.
world	World	The world this teacher will be evaluated in.
리턴	System

Called at every step in the world. Given the sensor input, returns the change in orientation and velocity in the range [0,1].

public activateNetwork ( double sensors ) : ISignalArray
sensors	double
리턴	ISignalArray

public double[] _prevState
리턴	double[]