Accession Number : ADA294066
Title : Learning Sequential Decision Rules, Using Simulation Models and Competition,
Corporate Author : NAVAL RESEARCH LAB WASHINGTON DC
Personal Author(s) : Grefenstette, John J. ; Ramsey, Connie L. ; Schultz, Alan C.
PDF Url : ADA294066
Report Date : 23 MAR 1990
Pagination or Media Count : 26
Abstract : The problem of learning decision rules for sequential tasks is addressed, focusing on the problem of learning tactical decision rules from a simple flight simulator. The learning method relies on the notion of competition and employs genetic algorithms to search the space of decision policies. Several experiments are presented that address issues arising from differences between the simulation model on which learning occurs and the target environment on which the decision rules are ultimately tested. (AN)
Descriptors : *ALGORITHMS, *RULE BASED SYSTEMS, *DECISION THEORY, DATA BASES, COMPUTERIZED SIMULATION, OPTIMIZATION, COMPETITION, LESSONS LEARNED, DECISION MAKING, LEARNING MACHINES, PROBLEM SOLVING, SEQUENTIAL ANALYSIS, CASE STUDIES, SEARCHING, DATA ACQUISITION, KNOWLEDGE BASED SYSTEMS, MANEUVERS, CONTROL THEORY, FLIGHT SIMULATORS, HIGH LEVEL LANGUAGES.
Subject Categories : Cybernetics
Distribution Statement : APPROVED FOR PUBLIC RELEASE