LEADER 05774nam 2200625Ia 450 001 9910511424003321 005 20201109180833.0 010 $a1-280-63604-1 010 $a9786610636044 010 $a0-08-046380-0 035 $a(CKB)1000000000357780 035 $a(EBL)274219 035 $a(SSID)ssj0000167304 035 $a(PQKBManifestationID)11170924 035 $a(PQKBTitleCode)TC0000167304 035 $a(PQKBWorkID)10168883 035 $a(PQKB)11680489 035 $a(MiAaPQ)EBC274219 035 $a(OCoLC)162587579 035 $a(CaSebORM)9780444527264 035 $a(PPN)221305459 035 $a(EXLCZ)991000000000357780 100 $a20060707d2006 uy 0 101 0 $aeng 135 $aurcn#nnn||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aHandbook of constraint programming$b[electronic resource] /$fedited by Francesca Rossi, Peter van Beek, Toby Walsh 205 $aFirst edition. 210 $aAmsterdam ;$aBoston $cElsevier$d2006 215 $a1 online resource (xi, 955 pages) $cillustrations 225 1 $aFoundations of artificial intelligence 311 $a0-444-52726-5 320 $aIncludes bibliographical references and index. 327 $aChapter 1. Introduction -- Chapter 2. Constraint satisfaction: an emerging paradigm -- Chapter 3. Constraint propagation -- Chapter 4. Backtracking search algorithms -- Chapter 5. Local search methods -- Chapter 6. Global constraints -- Chapter 7. Tractable structures for constraint satisfaction problems -- Chapter 8. The complexity of constraint languages -- Chapter 9. Soft constraints -- Chapter 10. Symmetry in constraint programming -- Chapter 11. Modelling -- Chapter 12. Constraint logic programming -- Chapter 13. Constraints in procedural and concurrent languages -- Chapter 14. Finite domain constraint programming systems -- Chapter 15. Operations research methods in constraint programming -- Chapter 16. Continuous and interval constraints -- Chapter 17. Constraints over structured domains -- Chapter 18. Randomness and structure -- Chapter 19. Temporal CSPs -- Chapter 20. Distributed constraint programming -- Chapter 21. Uncertainty and change -- Chapter 22. Constraint-based scheduling and planning -- Chapter 23. Vehicle routing -- Chapter 24. Configuration -- Chapter 25. Constraint applications in networks -- Chapter 26. Bioinformatics and constraints. 330 $aConstraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, computer science, databases, programming languages, and operations research. Constraint programming is currently applied with success to many domains, such as scheduling, planning, vehicle routing, configuration, networks, and bioinformatics. The aim of this handbook is to capture the full breadth and depth of the constraint programming field and to be encyclopedic in its scope and coverage. While there are several excellent books on constraint programming, such books necessarily focus on the main notions and techniques and cannot cover also extensions, applications, and languages. The handbook gives a reasonably complete coverage of all these lines of work, based on constraint programming, so that a reader can have a rather precise idea of the whole field and its potential. Of course each line of work is dealt with in a survey-like style, where some details may be neglected in favor of coverage. However, the extensive bibliography of each chapter will help the interested readers to find suitable sources for the missing details. Each chapter of the handbook is intended to be a self-contained survey of a topic, and is written by one or more authors who are leading researchers in the area. The intended audience of the handbook is researchers, graduate students, higher-year undergraduates and practitioners who wish to learn about the state-of-the-art in constraint programming. No prior knowledge about the field is necessary to be able to read the chapters and gather useful knowledge. Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas. The handbook is organized in two parts. The first part covers the basic foundations of constraint programming, including the history, the notion of constraint propagation, basic search methods, global constraints, tractability and computational complexity, and important issues in modeling a problem as a constraint problem. The second part covers constraint languages and solver, several useful extensions to the basic framework (such as interval constraints, structured domains, and distributed CSPs), and successful application areas for constraint programming. - Covers the whole field of constraint programming - Survey-style chapters - Five chapters on applications. 410 0$aFoundations of artificial intelligence (Elsevier) 606 $aConstraint programming (Computer science) 606 $aComputer programming 608 $aElectronic books. 615 0$aConstraint programming (Computer science) 615 0$aComputer programming. 676 $a005.116 700 $aRossi$b Francesca$0420890 701 $aRossi$b Francesca$f1962-$0768818 701 $aVan Beek$b Peter$01067910 701 $aWalsh$b Toby$01067911 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910511424003321 996 $aHandbook of constraint programming$92552187 997 $aUNINA LEADER 05302nam 22007095 450 001 9910300373303321 005 20200704030131.0 010 $a1-4614-8702-1 024 7 $a10.1007/978-1-4614-8702-9 035 $a(CKB)3710000000073903 035 $a(EBL)1592907 035 $a(SSID)ssj0001067662 035 $a(PQKBManifestationID)11607083 035 $a(PQKBTitleCode)TC0001067662 035 $a(PQKBWorkID)11091529 035 $a(PQKB)10389744 035 $a(MiAaPQ)EBC1592907 035 $a(DE-He213)978-1-4614-8702-9 035 $a(PPN)176099433 035 $a(EXLCZ)993710000000073903 100 $a20131126d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMathematical Biophysics /$fby Andrew Rubin, Galina Riznichenko 205 $a1st ed. 2014. 210 1$aNew York, NY :$cSpringer US :$cImprint: Springer,$d2014. 215 $a1 online resource (274 p.) 225 1 $aBiological and Medical Physics, Biomedical Engineering,$x1618-7210 300 $aDescription based upon print version of record. 311 $a1-322-33274-6 311 $a1-4614-8701-3 320 $aIncludes bibliographical references and index. 327 $aPreface -- Part I Basic models in mathematical biophysics -- Chapter 1 Growth and catalysis models -- Chapter 2 Oscillations, rhythms and chaos in biological systems -- Chapter 3 Spatiotemporal self-organization of biological systems -- Chapter 4 Model of the impact of a weak electric field on the nonlinear system of trans-membrane ion transport -- Part II Models of complex systems -- Chapter 5 Oscillations and periodic space structures of pH and electric potential along the cell membrane of algae Chara corallina -- Chapter 6 Models of Morphogenesis -- Chapter 7 Autowave processes, nerve pulse propagation, and heart activity -- Chapter 8 Nonlinear models of DNA dynamics -- Part III Kinetic models of photosynthetic processes -- Chapter 9 Models of photosynthetic electron transport. Electron transfer in a multienzyme complex -- Chapter 10 Kinetic model of interaction of two photosystems -- Chapter 11 Detailed model of electron transfer in PSII -- Chapter 12 Generalized kinetic model of primary photosynthetic processes -- Part IV Direct multiparticle models of processes in subcellular systems -- Chapter 13 Method of direct multiparticle simulation of protein interactions -- Chapter  14 Modeling of protein complex formation in solution with diffusion and electrostatic interactions -- Chapter 15 Modeling of protein interactions in photosynthetic membrane -- Chapter 16 Spaciotemporal evolution of electrochemical potential ??H+ in photosynthetic membrane -- Conclusion -- References -- Index. 330 $aThis book presents concise descriptions and analysis of the classical and modern models used in mathematical biophysics. The authors ask the question "what new information can be provided by the models that cannot be obtained directly from experimental data?" Actively developing fields such as regulatory mechanisms in cells and subcellular systems and electron transport and energy transport in membranes are addressed together with more classical topics such as metabolic processes, nerve conduction and heart activity, chemical kinetics, population dynamics, and photosynthesis. The main approach is to describe biological processes using different mathematical approaches necessary to reveal characteristic features and properties of simulated systems. With the emergence of powerful mathematics software packages such as MAPLE, Mathematica, Mathcad, and MatLab, these methodologies are now accessible to a wide audience. Provides succinct but authoritative coverage of a broad array of biophysical topics and models Written by authors at Moscow State University with its strong tradition in mathematics and biophysics Scope, coverage, and length make the book highly suitable for use in a one-semester course at the senior undergraduate/graduate level. 410 0$aBiological and Medical Physics, Biomedical Engineering,$x1618-7210 606 $aBiophysics 606 $aBiophysics 606 $aBioinformatics 606 $aComputational biology 606 $aChemometrics 606 $aBiological and Medical Physics, Biophysics$3https://scigraph.springernature.com/ontologies/product-market-codes/P27008 606 $aComputer Appl. in Life Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/L17004 606 $aMath. Applications in Chemistry$3https://scigraph.springernature.com/ontologies/product-market-codes/C17004 615 0$aBiophysics. 615 0$aBiophysics. 615 0$aBioinformatics. 615 0$aComputational biology. 615 0$aChemometrics. 615 14$aBiological and Medical Physics, Biophysics. 615 24$aComputer Appl. in Life Sciences. 615 24$aMath. Applications in Chemistry. 676 $a571.4 676 $a574.0151 700 $aRubin$b Andrew$4aut$4http://id.loc.gov/vocabulary/relators/aut$0791308 702 $aRiznichenko$b Galina$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910300373303321 996 $aMathematical Biophysics$92541341 997 $aUNINA