DocumentCode
1803830
Title
Convergence of critic-based training
Author
Prokhorov, Dana V. ; Wunsch, Donald C., II
Author_Institution
Dept. of Electr. Eng., Texas Tech. Univ., Lubbock, TX, USA
Volume
4
fYear
1997
fDate
12-15 Oct 1997
Firstpage
3057
Abstract
The paper discusses convergence issues when training adaptive critic designs (ACD) to control dynamic systems expressed as Markov sequences. We critically review two published convergence results of critic based training and propose to shift emphasis towards more practically valuable convergence proofs. We show a possible way to prove convergence of ACD training
Keywords
Markov processes; adaptive systems; learning (artificial intelligence); neural nets; ACD training; Markov sequences; adaptive critic designs; convergence issues; convergence proofs; critic based training; dynamic systems control; neural networks; Adaptive control; Computational intelligence; Convergence; Costs; Counting circuits; Laboratories; Optimal control; Programmable control; Resonance light scattering; Symmetric matrices;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location
Orlando, FL
ISSN
1062-922X
Print_ISBN
0-7803-4053-1
Type
conf
DOI
10.1109/ICSMC.1997.633056
Filename
633056
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