Reinforcement Learning Toolbox 2.0
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CQLearner Class Reference

Class for Q-Learning. More...

#include <ctdlearner.h>

Inheritance diagram for CQLearner:

CTDLearner CSemiMDPRewardListener CErrorSender CSemiMDPListener CParameterObject CParameters List of all members.


Public Member Functions

  CQLearner (CRewardFunction *rewardFunction, CAbstractQFunction *qfunction)
  ~CQLearner ()

Detailed Description

Class for Q-Learning.

Q-Learning chooses always the best action for the state s_{t+1}, which doesn't have to be the action executed in the state s_{t+1}, since exploration policies might choose another action. So Q-Learning is Off-Policy learning, it doesn’t learn a the values for the agent's policy, but for the optimal policy.

The class is just a normal TD-Learner, initializing the estimation policy with a CQGreedyPolicy object.


Constructor & Destructor Documentation

CQLearner::CQLearner CRewardFunction rewardFunction,
CAbstractQFunction qfunction
 
CQLearner::~CQLearner  ) 
 

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