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References

[1] Atkeson, C. G., and Reinkensmeyer, D. J., Using Associative Content-Addressable Memories To

Control Robots. Proc. of the IEEE Intern. Conf. on Robotics and Automation, Scottsdale, Az.,

USA, May 1989.

[2] Chen, C.C., and Pao, Y., Learning Control with Neural Networks. Proc. of the 1989 IEEE International

Conference on Robotics and Automation, Vol. 3, pp 1448-1453, 1989.

[3] Chen, F. C., Back-propagation Neural Network for Nonlinear Self-tuning Adaptive Control. Proc. of the

IEEE Intern. Symp. on Intelligent Control, Albany, NY, USA, September 1989.

[4] Devore, J. L., Probability & Statistics for Engineering and the Sciences. Brooks/Cole Monterey, Ca., USA,

1982

[5] Elsley, R. K., A Learning Architecture for Control Based on Back-propagation Neural Networks.

Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego, Ca., USA, 1988.

[6] Fu, K. S., Gonzalez, R. C., and Lee, C. S. G., Robotics, Control, Sensing, Vision, and Intelligence.

McGraw-Hill Book Company, New York, NY, USA, 1987

[7] Graf, D. H., and LaLonde, W. R., The Design of An Adaptive Neural Controller for Collision-Free

Movement of General Robot Manipulators. Proc. of the INNS, Boston, Mass. USA, September 1988.

[8] Graf, D. H., and LaLonde, W. R., A Neural Controller For Collision-Free Movement of General

Robot Manipulators. Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego, Ca., USA,

1988.

[9] Guez, A., and Ahmad, Z., Solution to the Inverse Kinematics Problem in Robotics by Neural Networks.

Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego, Ca., USA, 1988.

[10] Guez, A., and Ahmad, A., Solution to the Inverse Kinematics Problem in Robotics by Neural Networks.

Proc. of the INNS, Boston, Mass., USA, September 1988.

[11] Guez, A., Eilbert, J., and Kam M., Neuromorphic Architecture For Adaptive Robot Control: A

Preliminary Analysis. Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego, Ca., USA, 1987.

[12] Guez, A., and Selinsky, J., A Neuromorphic Controller with a Human Teacher. Proc. of the IEEE Intern. Conf.

on Neural Networks, San Diego, Ca., USA, 1988.

[13] Guez, A., and Selinsky, J., A Trainable Controller Based on Neural Networks. Proc. of the INNS, Boston,

Mass., USA, September 1988.

[14] Guyon, I., Neural Network Systems. Proc. of the INME Symposium, Lausanne, France.

[15] Guyon, I., Poujard, I., Personnaz, L., Dreyfus, G., Denker, J., and LeCun, Y., Comparing

Different Neural Architectures for Classifying Handwritten Digits. Proc. of Intern. Jt. Conf. on Neural

Networks (IJCNN), Washington, DC, USA, 1989.

[16] Handelman, D. A., Lane, S. H., and Gelfand, J. J., Integrating Neural Networks and Knowledge-Based

Systems For Robotic Control. Proc. of the IEEE Intern. Conf. on Robotics and Automation, Scottsdale, Az.,

USA, May 1989.

[17] Helferty, J. J., Collins, J. B., and Kam M., A Neural Network Learning Strategy For The Control

of a One-Legged Hopping Machine. Proc. of the IEEE Intern. Conf. on Robotics and Automation, Scottsdale,

Az., USA, May 1989.

[18] Hopfield, J. J., Neural Networks and Physical Systems with Emergent Collective Computational

Abilities. Proc. of the Nat. Acad. of Sciences, vol. 79, pp 2554 - 2558.

[19] Jorgensen, C., Neural Network Representation of Sensor Graphs in Autonomous Robot Path Planning.

Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego, Ca., USA, 1987.

[20] Josin, G., Neural-Space Generalization of a Topological Transformation. Biological Cybernetics, vol.59,

pp 283 - 290, 1988.

[21] Josin, G., Neural Network For Electrical and Computer Engineering. Proc. of Conf. on Electrical and

Computer Engineering, Vancouver, British Columbia, Canada, November 1988.

[22] Josin, G., Charney, D., and White, D., A Neural-Representation of an Unknown Inverse Kinematic

Transformation. Proceedings nEuro 88 - First European Conference on Neural Networks, Paris, France,

June 1988.

[23] Josin, G., Charney, D., and White, D., A Robot Control Strategy Using Neural Networks. Proc. of the INNS,

Boston, Mass., USA, September 1988.

[24] Josin, G., Charney, D. and White, D., Robotic Control Using Neural Networks. Proc. of the IEEE Intern. Conf.

on Neural Networks, San Diego, California, USA, July 1988.

[25] Karsai, G., Andersen, K, Cook, G. E., and Ramaswamy, K., Dynamic modelling and control of Nonlinear

Processes Using Neural Network Techniques. Proc. of the IEEE Intern. Symp. on Intelligent Control, Albany,

NY, USA, September 1989.

[26] Kawato, M., Furukawa, K., and Suzuki, R., A Hierarchical Neural-Network Model for control and

Learning of Voluntary Movement. Bio. Cybern., vol. 57,pp 169 - 185, 1987.

[27] Kawato, M., Setoyama, T., and Suzuki, R., Feedback Error Learning of Movement by Multi-Layer Neural

Network. Proc. of the INNS, Boston, Mass., USA, September 1988.

[28] Kawato, M., Uno, Y., and Isobe, M., A Hierarchical Model for Voluntary Movement and its

Application to Robotics. Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego, Ca., USA, 1987.

[29] Kinser, J. M., Caulfield, H. J., and Hester, C., Error-Correcting Neural Networks. Proc. of the INNS,

Boston, Mass., USA, September 1988.

[30] Kitamura, S., Kurematsu, Y., and Nakai, Y., Application of the Neural Network for the Trajectory

Planning of a Biped Locomotive Robot. Proc. of the INNS, Boston, Mass., USA, September 1988.

[31] Kohonen, T., Self-organized Formation of Typologically Correct Feature Maps. Biological Cybernetics,

vol. 43, pp 59 - 69.

[32] Kung, S. Y., and Hwang, J. N., An Algebraic Analysis for Optimal Hidden Units Size and Learning

Rates in Back-Propagation Learning, Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego,

Ca, USA, 1988.

[33] Kung, S. Y., K., and Hwang, J. N., Neural Network Architectures for Robotic Applications. IEEE

Trans. on Robotics and Automation, vol. 5., no. 5, pp. 641 - 657, October 1989.

[34] Kuntze, H. B., Position Control of Industrial Robots - Impacts, Concepts and Results in Robot Control

1988 (SYROCO’88) (ed. U. Rembold), Pergamon Press, 1989.

[35] Kuperstein, M., and Wang, J., Neural Controller for Adaptive Movements with Unforeseen Payloads.

IEEE Trans. on Neural Networks, vol. 1, no. 1, March 1990.

[36] Lee, D.M.A., Jack, H., ElMaraghy, W.H., and Buchal, R.O., Error Compensation Networks for Feedforward

Neural Networks, to be published.

[37] Lippman, R. P., An Introduction to Computing with Neural Nets. IEEE ASSP Magazine, vol. 4

no. 2, pp 4 - 22, April 1987.

[38] Marko, K. A., and Feldkamp, L. A., Automotive Diagnostics Using Neural Networks. Tutorial presented on

Neural Networks: Opportunities and Applications in Manufacturing, Detroit (Novi Hilton), Mich, USA, April

1990.

[39] Martinetz, T. M., Ritter, H. J., Schulten, K. J., Three-Dimensional Neural Net for Learning Visomotor

Coordination of a Robot Arm. IEEE Trans. on Neural Networks, vol. 1, no. 1, March 1990.

[40] Miller, W. T., Real Time Learned Sensor Processing and Motor. Proc. of the INNS, Boston, Mass., USA,

September 1988.

[41] Miller, W. T., Hewes, R. P, Glanz, F. H., and Kraft, L. G., Real-Time Dynamic Control of an Industrial

Manipulator Using a Neural-Network-Based Learning Controller. IEEE Trans. on Robotics and

Automation, vol. 6, no.1, pp 1 - 9, February 1990.

[42] Minsky, M. L., and Papert, S. A., Perceptrons. MIT Press, 1969.

[43] Moore, W. R., Conventional Fault-Tolerance and Neural Computers in NATO ASI Series, Vol. F41,

Neural Computers (eds. R. Eckmiller, and Ch. v. d. Malsburg), Springer-Verlag Berlin Heidelberg, 1988.

[44] Murugesan, S., Application of AI to Real-Time Intelligent Attitude Control of a Spacecraft. Proc. of the

IEEE Intern. Symp. on Intelligent Control, Albany, NY, USA, September 1989.

[45] Nagata, S., Kimoto, T., and Asakawa, K., Control of Mobile Reports With Neural Networks. Proc.

of the INNS, Boston, Mass., USA, September 1988.

[46] Narendra, K. S., and Parthasarathy, K., Identification and control of Dynamical Systems Using

Neural Networks. IEEE Trans. on Neural Networks, vol. 1, no. 1, March 1990.

[47] Neural Networks. a collection of articles in Byte, pp 216 - 245, August 1989.

[48] Pabon, J., and Gossard. D., The Role of Hidden Layers in Learning Motor Control in Autonomous

Systems. Proc. of the INNS, Boston, Mass., USA, September 1988.

[49] Pomerleau, D. A., Gusciora, G. L., Touretzky, D. S., and Kung, H. T., Neural Network Simulation at

Warp Speed: How We Got 17 Million Connections Per Seconds. Proc. of the IEEE Intern. Conf. on Neural

Networks, San Diego, Ca., USA, 1988.

[50] Pourboghrat, F., and Sayeh, M. R., Neural Network Learning Controller for Manipulators. Proc. of the INNS,

Boston, Mass., USA, September 1988.

[51] Psaltis, D., Sideris, A., Yamamura, A., Neural Controllers. IEEE First Intern. Conf. on Neural

Networks, vol. 4, pp 551 - 558, 1987.

[52] Ranky, P. G., and Ho, C. Y., Robot Modelling: Control and Applications with Software.

IFS (Publications) Ltd., UK, 1985.

[53] Reber, W. L., and Lyman, J., An Artificial Neural System Design For the Rotation and Scale

Invariant Pattern Recognition. IEEE First Intern. Conf. on Neural Networks, vol. 4, pp 277 - 283,

1987.

[54] Ritter, H., and Schulten, K., Kohonen’s Self-Organizing Maps: Exploring Their Computational

Capabilities. Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego, Ca., USA, 1988.

[55] Ritter, H., and Schulten, K., Topology Conserving Mappings for Learning Motor Tasks. AIP Conference

Proceedings 151 in Neural Networks For Computing (ed. J. S. Denker), 1986.

[56] Rumelhart, D. E., Hinton, G. E., and Williams, R. J., Learning Internal Representations by Error Propagation.

in Parallel Distributed Processing (eds. D. E. Rumelhart and J. L. McClellend) vol. 1, MIT Press, 1986.

[57] Rumelhart, D. E., and McClelland, J. L., Parallel Distributed Processing. vol. 1, MIT Press,

1986.

[58] Sanner, R. M., and Akin, D. L., Neuromorphic Regulation of Dynamic Systems Using Back Propagation.

Proc. of the INNS, Boston, Mass., USA, September 1988.

[59] Savic, M., and Tan, S. H., A New Class of Neural Networks Suitable For Intelligent Control. Proc. of the IEEE

Intern. Symp. on Intelligent Control, Albany, NY, USA, September 1989.

[60] Sobajic, D. J., Lu, J. J., and Pao, Y. H., Intelligent Control of the Intelledex 605T Robot Manipulator.

Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego, Ca., USA, 1988.

[61] Suddarth, S. C., Sutton, S. A., and Holden, A. D. C., A Symbolic-Neural Method for Solving Control

Problems. Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego, Ca., USA, 1988.

[62] Tawel, R., and Thakoor, A. P., Neural Networks For Robotic Control. Proc. of the INNS, Boston,

Mass., USA, September 1988.

[63] Ten Dyke, R. P., Neural Networks and Adaptive Control. Tutorial presented on Neural Networks:

Opportunities and Applications in Manufacturing, Detroit (Novi Hilton), Mich. USA, April 1990.

[64] Tolat, V.V., and Widrow, B., An Adaptive "Broom Balancer" with Visual Inputs. Proc. of the IEEE Intern.

Conf. on Neural Networks, San Diego, Ca., USA, 1988.

[65] Tourassis, V. D., and Ang, M. H., A Modular Architecture for Inverse Robot Kinematics.

IEEE Trans. on Robotics and Automation, vol. 5, no. 5, pp 555 - 568, October 1989.

[66] Troudet, T., and Merril, W. C., Neuromorphic Learning of Continuous-Valued Mappings in the

Presence of Noise. Proc. of the IEEE Intern. Symp. on Intelligent Control, Albany, NY, USA, September 1989.

[67] Tsutsumi, K., Katayama, K., and Matsumoto, H., Neural Computation for Controlling the Configuration

of 2-Dimensional Truss Structure. Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego, Ca., USA,

1988.

[68] Tsutsumi, K., and Matsumoto, H., Neural Computation and Learning Strategy for Manipulator Position

Control. Proc. of the IEEE Intern. Conf. on Neural Networks, San Diego, Ca., USA, 1987.

[69] Wasserman, P. D., Neural Computing - Theory and Practice. Van Nostrand Reinhold, New York,

NY, USA, 1988.

[70] Werbos, P. J., Backpropagation and Neurocontrol: A Review and Prospectus. Proc. of the Intern. Jt.

Conf. on Neural Networks, Washington, DC, USA, 1989

[71] Werbos, P. J., Consistency of HDP Applied To A Simple Reinforcement Learning Problem. Neural

Networks, March 1990 (in press).

[72] Werbos, P. J., Neural Networks for Control and System Identification. Proc. of the IEEE/CDC (Tampa, Fla.,

USA meeting), New York, NY, USA, 1989.

[73] Werbos, P. J., Neural Networks For Robotics and Control in WESCON/89 Conference Record (IEEE),

North Hollywood, Ca., USA, 1989.

[74] Widrow, B., The Original Adaptive Broom Balancer. Proc. of the IEEE Intern. Symp. on Circuits and

Systems, Philadelphia, Pa., USA, May 1987.

[75] Yeung, D. Y., and Gekey, G. A., Using a Context Sensitive Learning Network for Robot Arm

Control. Proc. of the IEEE Intern. Conf. on Robotics and Automation, Scottsdale, Az, USA,

May 1989.

[76] Yu, Y. H., and Simmons, R. F., Extra Output Biased Learning. Proc. of the Intern. Jt. Conf. on Neural

Networks, San Diego, Ca., USA, June 1990.