Adaptive autonomous agent with verbal learning

Details Adaptive autonomous agent with verbal learning Adaptive autonomous agent with verbal learning

1995-05-26

1998-09-01

Downs, Robert W.

Data processing: artificial intelligence

Neural network

Learning task

706 25, 706 26, G06F 1518

Patent

active

058025065

ABSTRACT:
The invention is an autonomous adaptive agent which can learn verbal as well as nonverbal behavior. The primary object of the system is to optimize a primary value function over time through continuously learning how to behave in an environment (which may be physical or electronic). Inputs may include verbal advice or information from sources of varying reliability as well as direct or preprocessed environmental inputs. Desired agent behavior may include motor actions and verbal behavior which may constitute a system output and which may also function "internally" to guide external actions. A further aspect of the invention is an efficient "training" process by which the agent can be taught to utilize verbal advice and information along with environmental inputs.

REFERENCES:
patent: 4933871 (1990-06-01), DeSieno
patent: 5124918 (1992-06-01), Beer et al.
patent: 5172253 (1992-12-01), Lynne
patent: 5402521 (1995-03-01), Niida et al.
patent: 5420964 (1995-05-01), Sugasaka et al.
patent: 5448681 (1995-09-01), Khan
patent: 5515477 (1996-05-01), Sutherland
A.G. Barto et al., "Neuronlike Adaptive Elements Tant Can Solve Difficult Learning Control Problems," IEEE Trans. on Systems, Man, and Cybernetics, vol. SMC-13 (5), pp. 834-846, Sep. 1983.
W.R. Hutchison and K.R. Stephens, "Integration of Distributed and Symbolic Knowledge Representation," IEEE First Int'l. Conf. on Neural Networks, pp. II-395 to II-398, Jun. 1987.
P.J. Werbos, "Backpropagation and Neurocontrol: A Review and Prospectus," IEEE Int'l. Conf. on Neural Networks, pp. I-209 to I-216, Jun. 1989.
J. Schmidhuber, "An On-line Algorithm for Dynamic Reinforcement Learning and Planning in Reactive Environments," IEEE Int'l. Conf. on Neural Networks, pp. II-253 to II-258, Jun. 1990.
K.R. Stephens et al., "Dynamic resource allocation using adaptive networks,"Neurocomputing, vol. 2(1), pp. 9-16, Jun. 1990.
P.J. Werbos, "Consistency of HDP Applied to a Simple Reinforcement Learning Problem," Neural Networks, vol. 3(2), pp. 179-189, Dec. 1990.
J.C. Hoskins and D.M. Himmelblau, "Process Control via Artificial Neural Networks and Reinforcement Learning," Computers and Chemical Engineering, vol. 16(4), pp. 241-251, Dec. 1992.
B.L. Digney and M.M. Gupta, "A Distributed Adaptive Control System for a Quadruped Mobile Robot," Int'l. Conf. on Neural Networks, pp. 144-149, Mar. 1993.
H.S. Del Nero and J.R.C. Piqueira, "Cognitive Science and the Failure of Behaviorism: Quantum, classical and mind indeterminacies," Intl'l. Conf. on Systems, Man, and Cybernetics, vol. 4, pp. 638-643, Oct. 1993.
K. Otwell et al., "A Large-Scale Neural Network Application for Airline Seat Allocation," World Congress on Neural Networks, vol. 1, pp. I-145 to I-150, Jun. 1994.
R. Maclin and J.W. Shavlik, "Incorporating Advice into Agents that Learn from Reinforcements," Proc. 12th National Conf. on Artificial Intelligence, vol. 1, pp. 694-699, Dec. 1994.
D. Gachet et al., "Learning Emergent Tasks for an Autonomous Mobile Robot," Int'l. Conf. on Intelligent Robots and Systems, vol. 1, pp. 290-297, Sep. 1994.
A. Newell & H.A. Simon, "GPS, A Program that Simulates Human Thought," reprinted in Computers and Thought, AAAI Press, pp. 279-293, Dec. 1995.
Barto, Reinforcement Learning and Adaptive Critic Methods; D.A. White & D. Sofge (Eds.) Handbook of Intelligent Control; Van Nostrand, 1992, pp. 469-491.
Brooks, Elephants Don't Play Chess; Elsevier Science Publishers B.V. (North-Holland), 1990, pp. 3-15.
Caudill, Expert Networks; Byte, Oct. 1991, pp. 108-116.
Cecconi & Parisi, Neural Networks With Motivational Units; Institute of Psychology, National Research Council, pp. 346-355, 1993.
Skinner, Verbal Behavior; Language, vol. 35, No. 1 (1959), pp. 26-59.
Donahoe & Palmer, Learning and Complex Behavior; 1994, pp. (ii-ix) 270-323.
Epstein, Generativity Theory and Education; Educational Technology, Oct. 1993, pp. 40-45.
Fahner and Eckmiller, Structural Adaptation of Parsimonious High-Order Neural Classifiers; Neural Networks, vol. 7, No. 2, 1994, pp. 279-289.
Hinton and Becker, Using Coherence Assumptions to Discover the Underlying Causes of the Sensory Input; Connectionism Theory and Practice (Davis, Ed.), 1992, pp. 3-21.
Lin, L., "Programming Robots Using Reinforcement Learning and Teaching," Proc. Ninth National Conf. on Artificial Intelligence, 1991, pp. 781-786.
Redding, Kowalczyk, and Downs, Constructive Higher-Order Newwork Algorithm That Is Polynomial Time; 1993, Neural Networks, vol. 6, pp. 997-1010.
St. John, Learning Language in the Service of a Task; Department of Cognitive Science, U. of C, San Diego, pp. 271-276, 1992.
Skinner, Verbal Behavior; Prentice-Hall, Inc., pp. ix, 1-453, 1957.
Sutton, Temporal Credit Assignment in Reinforcement Learning (Delayed Reinforcement); 1984, pp. 92-98.
Whitehead, A Complexity Analysis of Cooperative Mechanisms in Reinforcement Learning, Learning and Evaluation Functions, pp. 607-613, Proc. 9th Conf on A.I., 1991.

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