AForge.MachineLearning.QLearning.UpdateState C# (CSharp) Method

		public void UpdateState( int previousState, int action, double reward, int nextState )
		{
            // next state's action estimations
            double[] nextActionEstimations = qvalues[nextState];
			// find maximum expected summary reward from the next state
            double maxNextExpectedReward = nextActionEstimations[0];

			for ( int i = 1; i < actions; i++ )
			{
				if ( nextActionEstimations[i] > maxNextExpectedReward )
					maxNextExpectedReward = nextActionEstimations[i];
			}

            // previous state's action estimations
            double[] previousActionEstimations = qvalues[previousState];
            // update expexted summary reward of the previous state
            previousActionEstimations[action] *= ( 1.0 - learningRate );
            previousActionEstimations[action] += ( learningRate * ( reward + discountFactor * maxNextExpectedReward ) );
		}
	}