Missile defense and interceptor allocation by neuro-dynamic programming

Citation
Dp. Bertsekas et al., Missile defense and interceptor allocation by neuro-dynamic programming, IEEE SYST A, 30(1), 2000, pp. 42-51
Citations number
13
Language
INGLESE
art.tipo
Article
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS
ISSN journal
1083-4427 → ACNP
Volume
30
Issue
1
Year of publication
2000
Pages
42 - 51
Database
ISI
SICI code
1083-4427(200001)30:1<42:MDAIAB>2.0.ZU;2-L
Abstract
The purpose of this paper is to propose a solution methodology for a missil e defense problem involving the sequential allocation of defensive resource s over a series of engagements. The problem is cast as a dynamic programmin g/Markovian decision problem, which is computationally intractable by exact methods because of its large number of states and its complex modeling iss ues. We have employed a neuro-dynamic programming (NDP) framework, whereby the cost-to-go function is approximated using neural network architectures that are trained on simulated data. We report on the performance obtained u sing several different training methods, and we compare this performance wi th the optimal.