LEADER 02613nam 2200613Ia 450 001 9910451760203321 005 20200520144314.0 010 $a0-8166-8961-X 035 $a(CKB)1000000000346973 035 $a(EBL)310470 035 $a(OCoLC)227038300 035 $a(SSID)ssj0000283030 035 $a(PQKBManifestationID)11228223 035 $a(PQKBTitleCode)TC0000283030 035 $a(PQKBWorkID)10341507 035 $a(PQKB)10601348 035 $a(MiAaPQ)EBC310470 035 $a(MdBmJHUP)muse39645 035 $a(Au-PeEL)EBL310470 035 $a(CaPaEBR)ebr10151121 035 $a(CaONFJC)MIL522597 035 $a(EXLCZ)991000000000346973 100 $a19990527d1999 ub 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aPower and city governance$b[electronic resource] $ecomparative perspectives on urban development /$fAlan DiGaetano and John S. Klemanski 210 $aMinneapolis $cUniversity of Minnesota Press$dc1999 215 $a1 online resource (341 p.) 225 1 $aGlobalization and community ;$vv. 4 300 $aDescription based upon print version of record. 311 $a0-8166-3218-9 320 $aIncludes bibliographical references and index. 327 $aContents; Preface; Acknowledgments; Introduction; Part I: Comparing Urban Governance in the United Kingdom and the United States; Part II: Progrowth Politics; Part III: The Dilemmas of Progressive Urban Politics; Part IV: Modes of Governance as Explanation; Notes; References; Index 330 $aThis book develops a new way of comparing and understanding urban politics across national borders. The authors' approach, called "modes of governance," emphasizes governing alignments and their agendas. Applying this perspective to Boston and Detroit in the United States and Birmingham and Bristol in England, the authors compare the effects of postindustrial and urban political transformations, and link these to trends in the wider political economy. 410 0$aGlobalization and community ;$vv. 4. 606 $aCity planning$vCross-cultural studies 606 $aUrban policy$vCross-cultural studies 608 $aElectronic books. 615 0$aCity planning 615 0$aUrban policy 676 $a307.1/216 676 $a307.1216 700 $aDiGaetano$b Alan$0908595 701 $aKlemanski$b John S$0908596 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910451760203321 996 $aPower and city governance$92032110 997 $aUNINA LEADER 01096nam a2200325 i 4500 001 991000557729707536 005 20020509172223.0 008 010222s1971 it ||| | ita 035 $ab11376260-39ule_inst 035 $aPARLA210897$9ExL 040 $aDip.to Scienze Storiche Fil. e Geogr.$bita 082 0 $a330.1 100 1 $aGill, Richard T.$0126113 245 13$aLo sviluppo economico /$cRichard T. Gill 250 $a2. ed. 260 $aBologna :$bIl mulino,$c1971 300 $a196 p. ;$c22 cm. 440 3$aLa nuova scienza Serie di economia 500 $aTrad. G. Inzerilli 500 $aEd. italiana a cura di P. Pettenati 650 4$aSviluppo economico 700 1 $aPettenati, Paolo 700 1 $aInzerilli, Giorgio 740 0 $aEconomic development 907 $a.b11376260$b21-09-06$c01-07-02 912 $a991000557729707536 945 $aLE009 STOR.88.2-134$g1$i2009000036550$lle009$o-$pE0.00$q-$rl$s- $t0$u2$v0$w2$x0$y.i11559093$z01-07-02 996 $aSviluppo economico$9515474 997 $aUNISALENTO 998 $ale009$b01-01-01$cm$da $e-$fita$git $h3$i1 LEADER 04580nam 2200481 450 001 9910830945503321 005 20230629222455.0 010 $a1-119-78276-7 010 $a1-119-78277-5 010 $a1-119-78275-9 035 $a(CKB)4100000012037087 035 $a(MiAaPQ)EBC6735011 035 $a(Au-PeEL)EBL6735011 035 $a(OCoLC)1273975487 035 $a(EXLCZ)994100000012037087 100 $a20220626d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHuman-robot interaction control using reinforcement learning /$fWen Yu, Adolfo Perrusquia 210 1$aHoboken, New Jersey :$cIEEE Press :$cWiley,$d[2022] 210 4$dİ2022 215 $a1 online resource (289 pages) 225 1 $aIEEE Press series on systems science and engineering 311 $a1-119-78274-0 320 $aIncludes bibliographical references and index. 327 $aCover -- Title Page -- Copyright -- Contents -- Author Biographies -- List of Figures -- List of Tables -- Preface -- Part I Human?robot Interaction Control -- Chapter 1 Introduction -- 1.1 Human?Robot Interaction Control -- 1.2 Reinforcement Learning for Control -- 1.3 Structure of the Book -- References -- Chapter 2 Environment Model of Human?Robot Interaction -- 2.1 Impedance and Admittance -- 2.2 Impedance Model for Human?Robot Interaction -- 2.3 Identification of Human?Robot Interaction Model -- 2.4 Conclusions -- References -- Chapter 3 Model Based Human?Robot Interaction Control -- 3.1 Task Space Impedance/Admittance Control -- 3.2 Joint Space Impedance Control -- 3.3 Accuracy and Robustness -- 3.4 Simulations -- 3.5 Conclusions -- References -- Chapter 4 Model Free Human?Robot Interaction Control -- 4.1 Task?Space Control Using Joint?Space Dynamics -- 4.2 Task?Space Control Using Task?Space Dynamics -- 4.3 Joint Space Control -- 4.4 Simulations -- 4.5 Experiments -- 4.6 Conclusions -- References -- Chapter 5 Human?in?the?loop Control Using Euler Angles -- 5.1 Introduction -- 5.2 Joint?Space Control -- 5.3 Task?Space Control -- 5.4 Experiments -- 5.5 Conclusions -- References -- Part II Reinforcement Learning for Robot Interaction Control -- Chapter 6 Reinforcement Learning for Robot Position/Force Control -- 6.1 Introduction -- 6.2 Position/Force Control Using an Impedance Model -- 6.3 Reinforcement Learning Based Position/Force Control -- 6.4 Simulations and Experiments -- 6.5 Conclusions -- References -- Chapter 7 Continuous?Time Reinforcement Learning for Force Control -- 7.1 Introduction -- 7.2 K?means Clustering for Reinforcement Learning -- 7.3 Position/Force Control Using Reinforcement Learning -- 7.4 Experiments -- 7.5 Conclusions -- References -- Chapter 8 Robot Control in Worst?Case Uncertainty Using Reinforcement Learning. 327 $a8.1 Introduction -- 8.2 Robust Control Using Discrete?Time Reinforcement Learning -- 8.3 Double Q?Learning with k?Nearest Neighbors -- 8.4 Robust Control Using Continuous?Time Reinforcement Learning -- 8.5 Simulations and Experiments: Discrete?Time Case -- 8.6 Simulations and Experiments: Continuous?Time Case -- 8.7 Conclusions -- References -- Chapter 9 Redundant Robots Control Using Multi?Agent Reinforcement Learning -- 9.1 Introduction -- 9.2 Redundant Robot Control -- 9.3 Multi?Agent Reinforcement Learning for Redundant Robot Control -- 9.4 Simulations and experiments -- 9.5 Conclusions -- References -- Chapter 10 Robot ?2 Neural Control Using Reinforcement Learning -- 10.1 Introduction -- 10.2 ?2 Neural Control Using Discrete?Time Reinforcement Learning -- 10.3 ?2 Neural Control in Continuous Time -- 10.4 Examples -- 10.5 Conclusion -- References -- Chapter 11 Conclusions -- A Robot Kinematics and Dynamics -- A.1 Kinematics -- A.2 Dynamics -- A.3 Examples -- References -- B Reinforcement Learning for Control -- B.1 Markov decision processes -- B.2 Value functions -- B.3 Iterations -- B.4 TD learning -- Reference -- Index -- EULA. 410 0$aIEEE Press series on systems science and engineering. 606 $aHuman-robot interaction 615 0$aHuman-robot interaction. 676 $a629.8924019 700 $aYu$b Wen$c(Robotics engineer),$0760806 702 $aPerrusquia$b Adolfo 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830945503321 996 $aHuman-robot interaction control using reinforcement learning$94098966 997 $aUNINA