ISO learning approximates a solution to the inverse-controller problem in an unsupervised behavioral paradigm

Neural Computation

Volumn 15, Issue 4, 2003, Pages 865-884

  Porr, Bernd ^a   Von Ferber, Christian ^b   Wörgötter, Florentin ^a  

^a UNIVERSITY OF STIRLING   (United Kingdom)

^b UNIVERSITY OF FREIBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; FEEDBACK SYSTEM; MOTONEURON; PHYSIOLOGY; REFLEX; SENSORY NERVE CELL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; FEEDBACK; MOTOR NEURONS; NEURAL NETWORKS (COMPUTER); NEURONS, AFFERENT; REFLEX;

EID: 0038362695     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/08997660360581930     Document Type: Article

References (17)

1. Blinchikoff, H. J. (1976). Filtering in the time and frequency domain. New York: Wiley.
2. D'Azzo, J. J. (1988). Linear control system analysis and design. New York: McGraw-Hill.
3. Doetsch, G. (1961). Guide to the applications of the Laplace and z-transforms. New York: Van Nostrand Reinhold.
4. Ford, K. M., & Hayes, P. J. (Eds.). (1995). Android epistemology. Cambridge, MA: MIT Press.
5. Grüsser, O. (1986). Interaction of efferent and afferent signals in visual perception: A history of ideas and experimental paradigms. Acta Psychol., 63, 3-21.
6. Haruno, M., Wolpert, D. M., & Kawato, M. (2001). Mosaic model for sensorimotor learning and control. Neural Comp., 13, 2201-2220.
7. Luhmann, N. (1995). Social systems. Stanford, CA: Stanford University Press.
8. McGillem, C. D., & Cooper, G. R. (1984). Continuous and discrete signal and system analysis. New York: CBS Publishing.
9. Nise, N. S. (1992). Control systems engineering. New York: Cummings.
10. Palm, W. J. (2000). Modeling, analysis and control of dynamic systems. New York: Wiley.
11. Sollecito, W., & Reque, S. (1981). Stability. In J. Fitzgerald (Ed.), Fundamentals of system analysis. New York: Wiley.
12. Stewart, J. L. (1960). Fundamentals of signal theory. New York: McGraw-Hill.
13. Terrien, C. (1992). Discrete random signals and statistical signal processing. Upper Saddle River, NJ: Prentice Hall.
14. Verschure, P., & Voegtlin, T. (1998). A bottom-up approach towards the acquisition, retention, and expression of sequential representations: Distributed adaptive control III. Neural Networks, 11, 1531-1549.
15. von Glasersfeld, E. (1996). Learning and adaptation in constructivism. In L. Smith (Ed.), Critical readings on Piaget (pp. 22-27). London: Routledge.
16. von Uexküll, B. J. J. (1926). Theoretical biology. London: Kegan Paul, Trubner.
17. Wolpert, D. M., & Ghahramani, Z. (2000). Computational principles of movement neuroscience. Nature Neuroscience, 3 (Suppl.), 1212-1217.