LEADER 02839oam 2200637I 450 001 9910783732603321 005 20230214224032.0 010 $a1-134-92753-3 010 $a1-134-92754-1 010 $a1-138-13872-X 010 $a0-203-41308-3 010 $a1-280-32268-3 024 7 $a10.4324/9780203413081 035 $a(CKB)1000000000247775 035 $a(EBL)170016 035 $a(OCoLC)475877200 035 $a(SSID)ssj0000103133 035 $a(PQKBManifestationID)11132816 035 $a(PQKBTitleCode)TC0000103133 035 $a(PQKBWorkID)10061044 035 $a(PQKB)11400225 035 $a(MiAaPQ)EBC170016 035 $a(Au-PeEL)EBL170016 035 $a(CaPaEBR)ebr10058303 035 $a(CaONFJC)MIL32268 035 $a(OCoLC)50766715 035 $a(EXLCZ)991000000000247775 100 $a20180331d1994 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aAnalyzing qualitative data /$feditors, Alan Bryman, Robert G. Burgess 210 1$aLondon :$cRoutledge,$d1994. 215 $a1 online resource (247 pages) 300 $aDescription based upon print version of record. 311 0 $a0-415-06062-1 311 0 $a0-415-06063-X 320 $aIncludes bibliographical references at the end of each chapters and indexes. 327 $aBook Cover; Title; Contents; List of illustrations; Notes on contributors; Preface; Developments in qualitative data analysis: an introduction; Thinking through fieldwork; From field notes to dissertation: analyzing the stepfamily; Analyzing discourse; 'Second-hand ethnography': some problems in analyzing a feminist project; Linking qualitative and quantitative data analysis; Analyzing together: recollections of a team approach; Four studies from one or one study from four? Multi-site case study research; From filing cabinet to computer; Qualitative data analysis for applied policy research; Patterns of crisis behaviour: a qualitative inquiry Reflections on qualitative data analysis; Name index; Subject index 330 $aThis major inter-disciplinary collection is edited by two of the best respected figures in the field, and provides a superb general introduction to the analysis of qualitative data for all students. 606 $aSocial sciences$xStatistical methods 606 $aSocial sciences$xResearch$xMethodology 615 0$aSocial sciences$xStatistical methods. 615 0$aSocial sciences$xResearch$xMethodology. 676 $a300.15195 701 $aBryman$b Alan$0115648 701 $aBurgess$b Robert G$0122724 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910783732603321 996 $aAnalyzing qualitative data$93814521 997 $aUNINA LEADER 03340nam 22005055 450 001 9910409681503321 005 20251113191049.0 010 $a981-15-3231-1 024 7 $a10.1007/978-981-15-3231-3 035 $a(CKB)4100000010672249 035 $a(DE-He213)978-981-15-3231-3 035 $a(MiAaPQ)EBC6134215 035 $a(PPN)243224699 035 $a(EXLCZ)994100000010672249 100 $a20200313d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Behavior Design And Analysis $eA Consensus Perspective /$fby Yinyan Zhang, Shuai Li 205 $a1st ed. 2020. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2020. 215 $a1 online resource (XVII, 183 p. 44 illus., 38 illus. in color.) 311 08$a981-15-3230-3 327 $aChapter 1: Introduction to Collective Machine Behavior -- Chapter 2: Second-Order Min-Consensus -- Chapter 3: Consensus of High-Order Discrete-Time Multi-Agent Systems -- Chapter 4: Continuous-Time Biased Min-Consensus -- Chapter 5: Discrete-Time Biased Min-Consensus -- Chapter 6: Biased Consensus Based Distributed Neural Network -- Chapter 7: Predictive Suboptimal Consensus -- Chapter 8: Adaptive Near-Optimal Consensus. 330 $aIn this book, we present our systematic investigations into consensus in multi-agent systems. We show the design and analysis of various types of consensus protocols from a multi-agent perspective with a focus on min-consensus and its variants. We also discuss second-order and high-order min-consensus. A very interesting topic regarding the link between consensus and path planning is also included. We show that a biased min-consensus protocol can lead to the path planning phenomenon, which means that the complexity of shortest path planning can emerge from a perturbed version of min-consensus protocol, which as a case study may encourage researchers in the field of distributed control to rethink the nature of complexity and the distance between control and intelligence. We also illustrate the design and analysis of consensus protocols for nonlinear multi-agent systems derived from an optimal control formulation, which do not require solving a Hamilton-Jacobi-Bellman (HJB) equation. The book was written in a self-contained format. For each consensus protocol, the performance is verified through simulative examples and analyzed via mathematical derivations, using tools like graph theory and modern control theory. The book?s goal is to provide not only theoretical contributions but also explore underlying intuitions from a methodological perspective. 606 $aRobotics 606 $aMultiagent systems 606 $aRobotics 606 $aMultiagent Systems 615 0$aRobotics. 615 0$aMultiagent systems. 615 14$aRobotics. 615 24$aMultiagent Systems. 676 $a006.30285436 700 $aZhang$b Yinyan$4aut$4http://id.loc.gov/vocabulary/relators/aut$0946977 702 $aLi$b Shuai$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910409681503321 996 $aMachine Behavior Design And Analysis$92200057 997 $aUNINA