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010   $a3-030-12371-5
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035   $a(MiAaPQ)EBC5743342
035   $a(DE-He213)978-3-030-12371-0
035   $a(PPN)235232149
035   $a(EXLCZ)994930000000042103
100   $a20190330d2019      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aMany Agent Games in Socio-economic Systems: Corruption, Inspection, Coalition Building, Network Growth, Security /$fby Vassili N. Kolokoltsov, Oleg A. Malafeyev
205   $a1st ed. 2019.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019.
215   $a1 online resource (206 pages)
225 1 $aSpringer Series in Operations Research and Financial Engineering,$x1431-8598
300   $aIncludes index.
311   $a3-030-12370-7 
327   $a1. Introduction: Main Models and LLN Methology -- Part I: Multi-agent Interaction and Nonlinear Markov Games -- 2. Best Response Principals -- 3. Dynamic Control of Major Players -- 4. Models of Growth Under Pressure -- Par II: Pools of Rational Optimizers -- 5. MFGs for Finite-state Models -- 6. Three State Model of Corruption and Inspection -- 7. Four State Model of Cyber-security -- 8. Turnpick Theory for MFGs on Two-dimensional Networks.
330   $aThere has been an increase in attention toward systems involving large numbers of small players, giving rise to the theory of mean field games, mean field type control and nonlinear Markov games. Exhibiting various real world problems involving major and minor agents, this book presents a systematic continuous-space approximation approach for mean-field interacting agents models and mean-field games models. After describing Markov-chain methodology and a modeling of mean-field interacting systems, the text presents various structural conditions on the chain to yield respective socio-economic models, focusing on migration models via binary interactions. The specific applications are wide-ranging ? including inspection and corruption, cyber-security, counterterrorism, coalition building and network growth, minority games, and investment policies and optimal allocation ? making this book relevant to a wide audience of applied mathematicians interested in operations research, computer science, national security, economics, and finance.
410  0$aSpringer Series in Operations Research and Financial Engineering,$x1431-8598
606   $aGame theory
606   $aProbabilities
606   $aCalculus of variations
606   $aGame Theory, Economics, Social and Behav. Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/M13011
606   $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004
606   $aCalculus of Variations and Optimal Control; Optimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26016
615  0$aGame theory.
615  0$aProbabilities.
615  0$aCalculus of variations.
615 14$aGame Theory, Economics, Social and Behav. Sciences.
615 24$aProbability Theory and Stochastic Processes.
615 24$aCalculus of Variations and Optimal Control; Optimization.
676   $a300.15193
700   $aKolokoltsov$b Vassili N$4aut$4http://id.loc.gov/vocabulary/relators/aut$0441084
702   $aMalafeyev$b Oleg A$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910338256103321
996   $aMany Agent Games in Socio-economic Systems: Corruption, Inspection, Coalition Building, Network Growth, Security$92536865
997   $aUNINA