LEADER 01223nam--2200385---450- 001 990000992570203316 005 20100917121749.0 010 $a0-521-39288-8 035 $a0099257 035 $aUSA010099257 035 $a(ALEPH)000099257USA01 035 $a0099257 100 $a20020226d1992----km-y0itay0103----ba 101 $aeng 102 $aGB 105 $a||||||||001yy 200 1 $aPatronage and politics in the USSR$fJohn P. Willerton 210 $aCambridge$cCambridge University Press$d1992 215 $aXV, 305 p$d24 cm 225 2 $aSoviet and East European studies$v82 410 $12001$aSoviet and East European studies$v82 606 0 $aUnione sovietica$xPolitica$z1964- 676 $a324.204 700 1$aWILLERTON,$bJohn P.$0553037 801 0$aIT$bsalbc$gISBD 912 $a990000992570203316 951 $aXXX.B. Coll. 187/ 43 (COLL. MX 82)$b74829 EC$cXXX.B. Coll. 187/ 43 (COLL. MX)$d00289933 959 $aBK 969 $aECO 979 $aPATTY$b90$c20020226$lUSA01$h0945 979 $c20020403$lUSA01$h1741 979 $aPATRY$b90$c20040406$lUSA01$h1708 979 $aRSIAV4$b90$c20100917$lUSA01$h1217 996 $aPatronage and politics in the USSR$9975122 997 $aUNISA LEADER 03617nam 22007695 450 001 9910299701203321 005 20251113182106.0 010 $a9783319160009 010 $a3319160001 024 7 $a10.1007/978-3-319-16000-9 035 $a(CKB)3710000000360336 035 $a(EBL)1998048 035 $a(OCoLC)904131861 035 $a(SSID)ssj0001452113 035 $a(PQKBManifestationID)11889959 035 $a(PQKBTitleCode)TC0001452113 035 $a(PQKBWorkID)11498454 035 $a(PQKB)10813875 035 $a(DE-He213)978-3-319-16000-9 035 $a(MiAaPQ)EBC1998048 035 $a(PPN)184499143 035 $a(EXLCZ)993710000000360336 100 $a20150225d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aProbability Collectives $eA Distributed Multi-agent System Approach for Optimization /$fby Anand Jayant Kulkarni, Kang Tai, Ajith Abraham 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (162 p.) 225 1 $aIntelligent Systems Reference Library,$x1868-4408 ;$v86 300 $aDescription based upon print version of record. 311 08$a9783319159997 311 08$a3319159992 320 $aIncludes bibliographical references at the end of each chapters. 327 $aIntroduction to Optimization -- Probability Collectives: A Distributed Optimization Approach -- Constrained Probability Collectives: A Heuristic Approach -- Constrained Probability Collectives with a Penalty Function Approach -- Constrained Probability Collectives With Feasibility-Based Rule I -- Probability Collectives for Discrete and Mixed Variable Problems -- Probability Collectives with Feasibility-Based Rule II. 330 $aThis book provides an emerging computational intelligence tool in the framework of collective intelligence for modeling and controlling distributed multi-agent systems referred to as Probability Collectives. In the modified Probability Collectives methodology a number of constraint handling techniques are incorporated, which also reduces the computational complexity and improved the convergence and efficiency. Numerous examples and real world problems are used for illustration, which may also allow the reader to gain further insight into the associated concepts. 410 0$aIntelligent Systems Reference Library,$x1868-4408 ;$v86 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aSystem theory 606 $aMathematical physics 606 $aComputational Intelligence 606 $aArtificial Intelligence 606 $aComplex Systems 606 $aTheoretical, Mathematical and Computational Physics 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aSystem theory. 615 0$aMathematical physics. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aComplex Systems. 615 24$aTheoretical, Mathematical and Computational Physics. 676 $a006.3 700 $aKulkarni$b Anand Jayant$4aut$4http://id.loc.gov/vocabulary/relators/aut$0720592 702 $aTai$b Kang$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aAbraham$b Ajith$f1968-$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299701203321 996 $aProbability Collectives$92507771 997 $aUNINA