A. G. Barto's Publications, 1976-1993

Following is a list of A. G. Barto's publications 1976-1993 in chronological order. Some of these items appear both as published papers and as technical reports, but the title may have changed. In such cases, to avoid ambiguity, the citation shown in this list is the proper citation. We prefer that you cite the published version over the technical report.

To obtain copies of specific papers, please send email to mitchell [at] cs [dot] umass [dot] edu


  1. A. G. Barto. A neural network simulation method using the Fast Fourier Transform. IEEE Transactions on Systems, Man, and Cybernetics, SMC-5: 863-867, 1976.

  2. A. G. Barto. Discrete and continuous models. International Journal of General Systems, 4: 163-177, 1978.

  3. A. G.Barto. A note on pattern reproduction in tesselation structures. Journal of Computer and Systems Sciences, 16: 445-455, 1978.

  4. A. G. Barto, Invariant linear models of varying linear systems. NATO Conference Series, Series II, Systems Science, 5, G. Klir (Ed.), Plenum, New York, 1978.

  5. A. G. Barto and R. S. Sutton. Landmark learning: An illustration of associative search. Biological Cybernetics, 42: 1-8, 1981.

  6. A. G. Barto, R. S. Sutton and P. S. Brouwer. Associative search network: A reinforcement learning associative memory.Biological Cybernetics, 40: 201-211, 1981.

  7. R. S. Sutton and A. G. Barto. An adaptive network that constructs and uses an internal model of its environment. Cognition and Brain Theory, 4: 217-246, 1981.

  8. R. S. Sutton and A. G. Barto. Toward a modern theory of adaptive networks: Expectation and prediction. Psychological Review, 88: 135-171, 1981.

  9. A. G. Barto, C. W. Anderson, and R. S. Sutton. Synthesis of nonlinear control surfaces by a layered associative search network. Biological Cybernetics, 43: 175-185, 1982.

  10. A. G. Barto and R. S. Sutton. Simulation of anticipatory responses in classical conditioning by a neuron-like adaptive element. Behavioural Brain Research, 4: 221-235, 1982.

  11. A. G.Barto, R. S. Sutton and C. W. Anderson. Spatial learning simulation systems. Proceedings of the 10th IMACS World Congress on Systems Simulation and Scientific Computation, pp. 204-206, 1982.

  12. A. G. Barto and R. S. Sutton. Neural problem solving. COINS Technical Report 83-03, University of Massachusetts, 1983.

  13. A. G. Barto, R. S. Sutton and C. W. Anderson. Neuronlike elements that can solve difficult learning control problems. IEEE Transactions on Systems, Man, and Cybernetics, 13: 835-846, 1983.

  14. A. G. Barto. Adaptive neural networks for learning control: Some computational experiments. In Proceedings of the IEEE Workshop on Intelligent Control, Rensselaer Polytechnic Institute, Troy, NY, August 1985.

  15. A. G. Barto. Learning by statistical cooperation of self-interested neuron-like computing elements. Human Neurobiology, 4: 229-256, 1985. [pdf]

  16. A. G. Barto and P. Anandan. Pattern recognizing stochastic learning automata. IEEE Transactions on Systems, Man, and Cybernetics, 15: 360-375, 1985.

  17. A. G. Barto and C. W. Anderson. Structural learning in connectionist systems. In Proceedings of the Seventh Annual Conference of the Cognitive Science Society, Irvine, CA, August 1985.

  18. O. Selfridge, R. S. Sutton and A. G. Barto. Training and tracking in robotics. Proceedings of the Ninth International Joint Conference on Artificial Intelligence, pp. 670-672. San Mateo, CA: Morgan Kaufmann, 1985.

  19. A. G. Barto. Game-theoretic cooperativity in networks of self-interested units. In J. S. Denker, editor, Neural Networks for Computing, American Institute of Physics, New York, 1986.

  20. A. G. Barto, P. Anandan, and C. W. Anderson. Cooperativity in networks of pattern recognizing stochastic learning automata. In K. S. Narendra, editor, Adaptive and Learning Systems: Theory and Applications, Plenum, New York, 1986.

  21. J. W. Moore, J. E. Desmond, N. E. Berthier, E. J. Blazis, R. S. Sutton and A. G. Barto. Simulation of the classically conditioned nictitating membrane response by a neuron-like adaptive element. Response topography, neuronal firing, and interstimulus intervals. Behavioural Brain Research, 21: 143-154, 1986.

  22. A. G. Barto. An approach to learning control surfaces by connectionist systems. In M. A. Arbib and A. R. Hanson, editors, Vision, Brain and Cooperative Computation, MIT Press/ Bradford Books, Cambridge, MA, 1987.

  23. A. G. Barto and M. I. Jordan. Gradient following without back-propagation in layered networks. Proceedings of the First IEEE Annual Conference on Neural Networks, San Diego, CA, June 1987, pp. II-629-II-636.

  24. R. S. Sutton and A. G. Barto. A temporal-difference model of classical conditioning. TR87-509.2, Computer &Intelligent Systems Laboratory, GTE Laboratories Inc., Waltham, MA, 1987. [Also in Proceedings of the Ninth Annual Conference of the Cognitive Science Society, July, 1987.]

  25. A. Barto. From chemotaxis to cooperativity: Abstract exercises in neuronal learning strategies. In R. Durbin, C. Miall and G. Mitchison, editors, The Computing Neuron, pp. 73-98. Wokingham, England: Addison-Wesley, 1989.

  26. A. G. Barto. Connectionist learning for control. In W. T. Miller, R. S. Sutton and P. J. Werbos, editors, Neural Networks for Control, pp. 5-58. Cambridge, MA: The MIT Press, 1990. [Also appeared as COINS Technical Report 89-89, University of Massachusetts, 1989.]

  27. A. G. Barto and S. P. Singh. Reinforcement learning and dynamic programming. In Proceedings of the Sixth Yale Workshop on Adaptive and Learning Systems, New Haven, CT, August 1990. pp. 83-88.

  28. A. G. Barto and S. P. Singh. On the computational economics of reinforcement learning. In D.S. Touretzky, J.L. Elman, T.J. Sejnowski and G.E. Hinton, editors, Proceedings of the 1990 Connectionist Models Summer School. San Mateo, CA: Morgan Kaufmann, 1990. pp. 35-44.

  29. A. G. Barto, R. S. Sutton and C. J. C. H. Watkins. Learning and sequential decision making. In M. Gabriel and J. Moore, editors, Learning and Computational Neuroscience,The MIT Press, Cambridge, MA, 1990, pp. 539-602. [Also appeared as COINS Technical Report 89-95, University of Massachusetts, Amherst, MA, 1989.]

  30. A. G. Barto, R. S. Sutton and C. J. C. H. Watkins. Sequential decision problems and neural networks. In D. S. Touretzky, editor, Advances in Neural Information Processing Systems 2, pp. 686-693. Morgan Kaufmann Publishers, San Mateo, CA, 1990.

  31. J. C. Houk, S. P. Singh, C. Fisher and A. G. Barto. An adaptive sensorimotor network inspired by the anatomy and physiology of the cerebellum. In W. T. Miller, R. S. Sutton and P. J. Werbos, editors, Neural Networks for Control, pp. 301-348. Cambridge, MA: MIT Press, 1990. [Also appeared as COINS Technical Report 89-108, University of Massachusetts, 1989.]

  32. R. A. Jacobs, M. I. Jordan and A. G. Barto. Task decomposition through competition in a modular connectionist architecture: The what and where vision tasks. Cognitive Science, 15: 219-250, 1991. [Also appeared as COINS Technical Report 90-27, University of Massachusetts at Amherst, March 1990.]

  33. R. S. Sutton and A. G. Barto. Time-derivative models of Pavlovian reinforcement. In M. Gabriel and J. Moore, editors, Learning and Computational Neuroscience,The MIT Press: Cambridge, MA, 1990, pp. 497-537.

  34. R. C. Yee, S. Saxena, P. E. Utgoff and A. G. Barto. Explaining temporal differences to create useful concepts for evaluating states. In Proceedings of the 8th National Conference on Artificial Intelligence, pp. 882-888. AAAI Press/MIT Press, 1990.

  35. A.G. Barto. Some learning tasks from a control perspective. In L. Nadel and D. Stein, editors, 1990 Lectures in Complex Systems, Addison-Wesley, 1991. pp. 195-223. [Also appeared as COINS Technical Report 90-122, University of Massachusetts at Amherst, December 1990.]

  36. R. S. Sutton, A. G. Barto and R. J. Williams. Reinforcement learning is direct adaptive optimal control. Proceedings of the 1991 American Control Conference, June 26-28, Boston, MA. pp. 2143-2146.

  37. J. C. Houk and A. G. Barto. Distributed sensorimotor learning. In G. E. Stelmach and J. Requin, editors, Tutorials in Motor Behavior II, Elsevier Science Publishers B.V.: Amsterdam, 1992, pp. 71-100. (Also appeared as NPB Technical Report #1, Center for Neuroscience Research on Neuronal Populations and Behavior, Northwestern University, Dec. 1991.)

  38. V. Gullapalli, R. A. Grupen and A. G. Barto. Learning reactive admittance control. In Proceedings of the 1992 IEEE Conference on Robotics and Automation. Nice, France, May 1992, pp. 1475-1480.

  39. N.E. Berthier, S.P. Singh, A.G. Barto and J.C. Houk. A cortico-cerebellar model that learns to generate distributed motor commands to control a kinematic arm. In Neural Information Processing Systems 4, J.E. Moody, S.J. Hanson, and R.P. Lippmann (Eds.), Morgan Kaufmann: San Mateo, 1992, pp. 611-618.

  40. V. Gullapalli and A. G. Barto. Shaping as a method for accelerating reinforcement learning. In Proceedings of the 1992 IEEE International Symposium on Intelligent Control, Glasgow, Scotland, August 1992.

  41. A. G. Barto. Reinforcement learning and adaptive critic methods. In Handbook of Intelligent Control, D.A. White and D.A. Sofge, editors. New York: Van Nostrand Reinhold, 1992, pp. 469-491.

  42. A. G. Barto and S. J. Bradtke. Learning to solve stochastic optimal path problems using real-time dynamic programming. Proceedings of the Seventh Yale Workshop on Adaptive and Learning Systems, New Haven, CT, May 1992, pp. 143-148.

  43. A. G. Barto and V. Gullapalli. Neural networks and adaptive control. In P. Rudomin, M. A. Arbib, F. Cervantes-Perez, and R. Romo, editors, Neuroscience: From Neural Networks to Artificial Intelligence, Research Notes in Neural Computation, Vol. 4, Springer-Verlag, 1993. pp. 471-493. [Preprint appeared as NPB Technical Report 6, Center for Neuroscience Research on Neuronal Populations and Behavior, Northwestern University, March 1992.]

  44. N. E. Berthier, S. P. Singh, A. G. Barto, and J. C. Houk. Distributed representation of limb motor programs in arrays of adjustable pattern generators. Journal of Cognitive Neuroscience, 5 (1): 56-78, 1993. [Also appeared as NPB Technical Report #3, Center for Neuroscience Research on Neuronal Populations and Behavior, Northwestern University, 1991.]

  45. J. C. Houk, J. Kiefer, and A. G. Barto. Distributed motor commands in the limb premotor network. Trends in Neuroscience 16 (1): 27-33, 1993.


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