Accession Number : ADA294089
Title : Simulation-Assisted Learning by Competition. Effects of Noise Differences between Training Model and Target Environment,
Corporate Author : NAVAL RESEARCH LAB WASHINGTON DC
Personal Author(s) : Schultz, Alan C. ; Ramsey, Connie L. ; Grefenstette, John J.
PDF Url : ADA294089
Report Date : 1990
Pagination or Media Count : 6
Abstract : The problem of learning decision rules for sequential tasks is addressed, focusing on the problem of learning tactical plans from a simple flight simulator where a plane must avoid a missile. The learning method relies on the notion of competition and employs genetic algorithms to search the space of decision policies. 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. Specifically, either the model or the target environment may contain noise. These experiments examine the effect of learning tactical plans without noise and then testing the plans in a noisy environment, and the effect of learning plans in a noisy simulator and then testing the plans in a noise-free environment. (AN)
Descriptors : *LEARNING MACHINES, *RULE BASED SYSTEMS, DATA BASES, ALGORITHMS, COMPUTERIZED SIMULATION, SCENARIOS, EXPERIMENTAL DATA, OPTIMIZATION, COMPETITION, TRAINING, PROBLEM SOLVING, PLANNING, DECISION THEORY, SEARCHING, KNOWLEDGE BASED SYSTEMS, TACTICAL ANALYSIS, SYSTEMS ANALYSIS, NOISE REDUCTION, FLIGHT SIMULATORS, LEARNING.
Subject Categories : Cybernetics
Distribution Statement : APPROVED FOR PUBLIC RELEASE