| Tag |
First Indicator |
Second Indicator |
Subfields |
| LEADER |
00000cam a2200000Ka 4500 |
| 001 |
in00003506321 |
| 006 |
m o d |
| 007 |
cr unu---uuaua |
| 008 |
090131s1997 gw ob 001 0 eng d |
| 005 |
20260420215351.9 |
| 019 |
|
|
|a 321328526
|a 644086619
|a 664271622
|
| 020 |
|
|
|a 9783540409380 (electronic bk.)
|
| 020 |
|
|
|a 3540409386 (electronic bk.)
|
| 020 |
|
|
|z 3540761543
|
| 020 |
|
|
|z 9783540761549
|
| 035 |
|
|
|a (OCoLC)300727391
|z (OCoLC)321328526
|z (OCoLC)644086619
|z (OCoLC)664271622
|
| 040 |
|
|
|a OCLCE
|b eng
|e pn
|c OCLCE
|d OCL
|d CUSER
|d YNG
|d OCLCQ
|d GW5XE
|d OCLCF
|d OCLCQ
|d UtOrBLW
|
| 042 |
|
|
|a dlr
|
| 049 |
|
|
|a TXAM
|
| 050 |
|
4 |
|a T57.32
|b .P69 1997
|
| 082 |
0 |
4 |
|a 519.7
|2 21
|
| 084 |
|
|
|a 31.80
|2 bcl
|
| 084 |
|
|
|a SI 845
|2 rvk
|
| 100 |
1 |
|
|a Poznyak, Alexander S.
|
| 245 |
1 |
0 |
|a Learning automata and stochastic optimization /
|c A.S. Poznyak and K. Najim.
|
| 264 |
|
1 |
|a Berlin ;
|a New York :
|b Springer,
|c [1997]
|
| 264 |
|
4 |
|c ©1997
|
| 300 |
|
|
|a 1 online resource.
|
| 336 |
|
|
|a text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a computer
|b c
|2 rdamedia
|
| 338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
| 490 |
1 |
|
|a Lecture notes in control and information sciences ;
|v 225
|
| 504 |
|
|
|a Includes bibliographical references and index.
|
| 520 |
|
|
|a In the last decade there has been a steadily growing need for and interest in computational methods for solving stochastic optimization problems with or wihout constraints. Optimization techniques have been gaining greater acceptance in many industrial applications, and learning systems have made a significant impact on engineering problems in many areas, including modelling, control, optimization, pattern recognition, signal processing and diagnosis. Learning automata have an advantage over other methods in being applicable across a wide range of functions. Featuring new and efficient learning techniques for stochastic optimization, and with examples illustrating the practical application of these techniques, this volume will be of benefit to practicing control engineers and to graduate students taking courses in optimization, control theory or statistics.
|
| 538 |
|
|
|a Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
|u http://purl.oclc.org/DLF/benchrepro0212
|5 MiAaHDL
|
| 583 |
1 |
|
|a digitized
|c 2010
|h HathiTrust Digital Library
|l committed to preserve
|2 pda
|5 MiAaHDL
|
| 588 |
|
|
|a Description based on print version record.
|
| 500 |
|
|
|a Electronic resource.
|
| 650 |
|
0 |
|a Stochastic processes.
|
| 650 |
|
0 |
|a Mathematical optimization.
|
| 650 |
|
0 |
|a Machine learning.
|
| 650 |
|
0 |
|a Artificial intelligence.
|
| 650 |
|
4 |
|a optimisation sous contrainte.
|
| 650 |
|
4 |
|a optimisation sans contrainte.
|
| 650 |
|
4 |
|a optimisation mathématique.
|
| 650 |
|
4 |
|a automate apprentissage.
|
| 650 |
|
4 |
|a optimisation stochastique.
|
| 650 |
|
7 |
|a Artificial intelligence.
|2 fast
|0 (OCoLC)fst00817247
|
| 650 |
|
7 |
|a Machine learning.
|2 fast
|0 (OCoLC)fst01004795
|
| 650 |
|
7 |
|a Mathematical optimization.
|2 fast
|0 (OCoLC)fst01012099
|
| 650 |
|
7 |
|a Stochastic processes.
|2 fast
|0 (OCoLC)fst01133519
|
| 650 |
1 |
7 |
|a Optimaliseren.
|2 gtt
|
| 650 |
1 |
7 |
|a Automatentheorie.
|2 gtt
|
| 650 |
|
7 |
|a Optimisation mathématique.
|2 ram
|
| 650 |
|
7 |
|a Apprentissage automatique.
|2 ram
|
| 650 |
|
7 |
|a Intelligence artificielle.
|2 ram
|
| 650 |
0 |
7 |
|a Lernender Automat.
|2 swd
|
| 650 |
0 |
7 |
|a Stochastische Optimierung.
|2 swd
|
| 655 |
|
7 |
|a Electronic books.
|2 local
|
| 700 |
1 |
|
|a Najim, K.
|
| 710 |
2 |
|
|a SpringerLink (Online service)
|
| 776 |
1 |
8 |
|i Print version:
|a Poznyak, Alexander S.
|t Learning automata and stochastic optimization.
|d Berlin ; New York : Springer, ©1997
|z 3540761543
|z 9783540761549
|w (DLC) 97001897
|w (OCoLC)36417745
|
| 830 |
|
0 |
|a Lecture notes in control and information sciences ;
|v 225.
|
| 856 |
4 |
0 |
|u http://proxy.library.tamu.edu/login?url=https://link.springer.com/10.1007/BFb0015102
|z Connect to the full text of this electronic book
|t 0
|
| 994 |
|
|
|a 92
|b TXA
|
| 999 |
|
|
|a MARS
|
| 999 |
f |
f |
|s 96b40df7-0cb3-3b90-9ab1-34636efac8a6
|i 5f4dd4d8-10f2-3d64-ba9d-923c1b1c4c75
|t 0
|
| 952 |
f |
f |
|a Texas A&M University
|b College Station
|c Electronic Resources
|s www_evans
|d Available Online
|t 0
|e T57.32 .P69 1997
|h Library of Congress classification
|
| 998 |
f |
f |
|a T57.32 .P69 1997
|t 0
|l Available Online
|