Accession Number : ADA182969
Title : Explanation-Based Learning of Generalized Robot Assembly Plans.
Descriptive Note : Technical rept.,
Corporate Author : ILLINOIS UNIV AT URBANA COORDINATED SCIENCE LAB
Personal Author(s) : Segre,Alberto M.
Report Date : JAN 1987
Pagination or Media Count : 251
Abstract : This report describes an experiment involving the application of a recently developed machine learning technique, explanation-based learning, to the robot retraining problem. Explanation-based learning permits a system to acquire generalized problem-solving knowledge on the basis of a single observed problem-solving example. The resulting computer program, called ARMS for Acquiring Robotic Manufacturing Schemata, serves as a medium for discussing issues related to this particular type of learning. This work clarifies and extends the corpus of knowledge so that explanation-based learning can be successfully applied to real world problems. From a machine learning perspective, ARMS is one of the more ambitious working explanation-based learning implementations to date. Unlike many other vehicles for machine learning research, the ARMS system operates in a nontrivial domain conveying the flavor of a real robot assembly application. (Keywords: Artificial intelligence; Scenarios).
Descriptors : *COMPUTER PROGRAMS, *LEARNING MACHINES, *ROBOTS, WEAPON SYSTEMS, PLANNING, LEARNING, ARTIFICIAL INTELLIGENCE, RETRAINING, ASSEMBLY, SCENARIOS, THESES, PROBLEM SOLVING
Subject Categories : Cybernetics
Distribution Statement : APPROVED FOR PUBLIC RELEASE