Accession Number : ADA298853

Title :   Neural Networks that Create their Own Goals Using Growth Cycles.

Descriptive Note : Final rept.,

Corporate Author : SYMBUS TECHNOLOGY INC WALTHAM MA

Personal Author(s) : Kuperstein, Michael

PDF Url : ADA298853

Report Date : 02 DEC 1994

Pagination or Media Count : 13

Abstract : Over the past year our research on the generation and control of path planning has formed a new theory using neural networks that allows intelligent agents to automate sub-tasking in achieving desired goals. This theory called Growth Cycles provides functionality that will be crucial at the next stage of computing and communication systems with their exponentially increasing overhead. Distributed intelligent agents will begin to autonomously and adaptively maintain the huge and complex National Information Infrastructure. The specific research shows how an intelligent agent can learn to go from anywhere to anywhere around obstacles in novel and contingent environments. Although the research focuses on adaptive path planning, it can also be generalized and applied to adaptive and autonomous problem solving. The following paper details the entire effort for this contract and has been submitted for publication. (KAZR) p. 1

Descriptors :   *NEURAL NETS, CONTROL, GROWTH(GENERAL), THEORY, PATHS, CYCLES, PROBLEM SOLVING, PLANNING, ADAPTIVE SYSTEMS, SELF OPERATION, COMMUNICATION AND RADIO SYSTEMS, ARCHITECTURE.

Subject Categories : Cybernetics

Distribution Statement : APPROVED FOR PUBLIC RELEASE