Reinforcement Learning Toolbox 2.0 last updated:

General Documentation Manual Tutorial Class Reference Master Thesis Examples Related Papers Downloads Links News mailto:webmaster Main Page     Class Hierarchy   Compound List   File List   Compound Members   File Members CVFunctionGradientLearner Class Reference #include <cvfunctionlearner.h> Inheritance diagram for CVFunctionGradientLearner: List of all members. Public Member Functions   CVFunctionGradientLearner (CRewardFunction *rewardFunction, CGradientVFunction *vFunction, CResidualFunction *residual, CResidualGradientFunction *residualGradientFunction)   ~CVFunctionGradientLearner () virtual double  getTemporalDifference (CStateCollection *oldState, CAction *action, double reward, CStateCollection *nextState)   Calculates the temporal difference. Protected Member Functions virtual void  addETraces (CStateCollection *oldState, CStateCollection *newState, int duration)   adds the current state to the etrace object. Protected Attributes CResidualFunction *  residual CResidualGradientFunction *  residualGradientFunction CGradientVFunction *  gradientVFunction CGradientVETraces *  gradientETraces CFeatureList *  oldGradient CFeatureList *  newGradient CFeatureList *  residualGradient Constructor & Destructor Documentation CVFunctionGradientLearner::CVFunctionGradientLearner (  CRewardFunction *  rewardFunction, CGradientVFunction *  vFunction, CResidualFunction *  residual, CResidualGradientFunction *  residualGradientFunction )  CVFunctionGradientLearner::~CVFunctionGradientLearner (   )  Member Function Documentation virtual void CVFunctionGradientLearner::addETraces (  CStateCollection *  oldState, CStateCollection *  newState, int  duration )  [protected, virtual]   adds the current state to the etrace object. Reimplemented from CVFunctionLearner. virtual double CVFunctionGradientLearner::getTemporalDifference (  CStateCollection *  oldState, CAction *  action, double  reward, CStateCollection *  nextState )  [virtual]   Calculates the temporal difference. The temporal difference for the given step is td = r_t + gamma * V(s_{t+1}) - V(s_t) respectively td = r_t + gamma^N * V(s_{t+1}) - V(s_t) for multistep actions. Reimplemented from CVFunctionLearner. Member Data Documentation CGradientVETraces* CVFunctionGradientLearner::gradientETraces [protected] CGradientVFunction* CVFunctionGradientLearner::gradientVFunction [protected] CFeatureList* CVFunctionGradientLearner::newGradient [protected] CFeatureList* CVFunctionGradientLearner::oldGradient [protected] CResidualFunction* CVFunctionGradientLearner::residual [protected] CFeatureList* CVFunctionGradientLearner::residualGradient [protected] CResidualGradientFunction* CVFunctionGradientLearner::residualGradientFunction [protected] The documentation for this class was generated from the following file: cvfunctionlearner.h