Research ArticleOpen AccessGoogle Scholar indexed
The Computational Theory of Intelligence: Feedback
Quantitative Research, Institute of Trading and Finance, Montreal, Canada
- 1 Quantitative Research, Institute of Trading and Finance, Montreal, Canada
International Journal of Modern Nonlinear Theory and Application·Volume 06 (2017)·Pages 70–73·Published 14 June 2017·DOI10.4236/ijmnta.2017.62006
Copy link · social · email
Abstract
In this paper we discuss the applications of feedback to intelligent agents. We show that it adds a momentum component to the learning algorithm. We derive via Lyapunov stability theory the condition necessary in order that the entropy minimization principal of computational intelligence is preserved in the presence of feedback.
KeywordsNeural NetworksFeedbackIntelligenceComputationArtificial IntelligenceLyapunov Stability
- Kovach, D. (2014) The Computational Theory of Intelligence: Information Entropy. International Journal of Modern Nonlinear Theory and Application, 3, 182-190. https://doi.org/10.4236/ijmnta.2014.34020
- Kaastra, I. and Boyd, M. (1996) Designing a Neural Network for Forecasting Financial and Economic Time Series. Neurocomputing, 10, 215-236. https://doi.org/10.1016/0925-2312(95)00039-9
- Lee, K.Y., A. Sode-Yome, and June Ho Park. (1998) Adaptive Hopfield Neural Networks for Economic Load Dispatch IEEE Transactions on Power Systems, 13, 519-526.
- Istook, E. and Martinez, T. (2002) Improved Backpropagation Learning in Neural Networks with Windowed Momentum. International Journal of Neural Systems, 12, 303-318. https://doi.org/10.1142/S0129065702001114
- Bird, R.J. (2003) Chaos and Life: Complexity and Order in Evolution and Thought. Columbia University Press, New York. https://doi.org/10.7312/bird12662
- Latora, V., Baranger, M., Rapisarda, A. and Tsallis, C. (2000) The Rate of Entropy Increase at the Edge of Chaos. Physics Letters A, 273, 97-103. https://doi.org/10.1016/S0375-9601(00)00484-9
- Cencini, M., Cecconi, F. and Vulpiani, A. (2010) Chaos: From Simple Models to Complex Systems. World Scientific, Hackensack, NJ.