LEADER 01789oam 2200505 450 001 9910709869103321 005 20180727084524.0 035 $a(CKB)5470000002473564 035 $a(OCoLC)891572311$z(OCoLC)954273872 035 $a(OCoLC)995470000002473564 035 $a(EXLCZ)995470000002473564 100 $a20140929d1946 ua 0 101 0 $aeng 135 $aurbn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aReptilian fauna of the North Horn formation of central Utah /$fby Charles W. Gilmore 210 1$aWashington :$cUnited States Department of the Interior, Geological Survey,$d1946. 215 $a1 online resource (iii, 29-53 pages, 11 unnumbered plates) $cillustrations, maps 225 1 $aProfessional paper ;$v210-C 225 1 $aShorter contributions to general geology ;$v1946 300 $aTitle from title screen (viewed September 22, 2014). 320 $aIncludes bibliographical references and index. 517 3 $aShorter contributions to general geology, 1946 606 $aPaleontology$zUtah$zNorth Horn Formation 606 $aPaleontology$2fast 607 $aNorth Horn Formation (Utah) 607 $aUtah$2fast 607 $aUtah$zNorth Horn Formation$2fast 615 0$aPaleontology 615 7$aPaleontology. 700 $aGilmore$b Charles W$g(Charles Whitney),$f1874-1945,$01397936 702 $aCederstrom$b D. J$g(Dagfin John),$f1908-1997, 712 02$aGeological Survey (U.S.), 801 0$bCOP 801 1$bCOP 801 2$bOCLCO 801 2$bOCLCF 801 2$bOCLCE 801 2$bGPO 906 $aBOOK 912 $a9910709869103321 996 $aReptilian fauna of the North Horn formation of central Utah$93502605 997 $aUNINA LEADER 05525nam 22006735 450 001 9910144131803321 005 20200702165332.0 010 $a3-540-46417-4 024 7 $a10.1007/10719871 035 $a(CKB)1000000000548834 035 $a(SSID)ssj0000323860 035 $a(PQKBManifestationID)11241064 035 $a(PQKBTitleCode)TC0000323860 035 $a(PQKBWorkID)10303382 035 $a(PQKB)10127013 035 $a(DE-He213)978-3-540-46417-4 035 $a(MiAaPQ)EBC3088957 035 $a(PPN)155194364 035 $a(EXLCZ)991000000000548834 100 $a20121227d2000 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aHybrid Neural Systems /$fedited by Stefan Wermter, Ron Sun 205 $a1st ed. 2000. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2000. 215 $a1 online resource (XI, 401 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v1778 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-67305-9 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aAn Overview of Hybrid Neural Systems -- An Overview of Hybrid Neural Systems -- Structured Connectionism and Rule Representation -- Layered Hybrid Connectionist Models for Cognitive Science -- Types and Quantifiers in SHRUTI ? A Connectionist Model of Rapid Reasoning and Relational Processing -- A Recursive Neural Network for Reflexive Reasoning -- A Novel Modular Neural Architecture for Rule-Based and Similarity-Based Reasoning -- Addressing Knowledge-Representation Issues in Connectionist Symbolic Rule Encoding for General Inference -- Towards a Hybrid Model of First-Order Theory Refinement -- Distributed Neural Architectures and Language Processing -- Dynamical Recurrent Networks for Sequential Data Processing -- Fuzzy Knowledge and Recurrent Neural Networks: A Dynamical Systems Perspective -- Combining Maps and Distributed Representations for Shift-Reduce Parsing -- Towards Hybrid Neural Learning Internet Agents -- A Connectionist Simulation of the Empirical Acquisition of Grammatical Relations -- Large Patterns Make Great Symbols: An Example of Learning from Example -- Context Vectors: A Step Toward a ?Grand Unified Representation? -- Integration of Graphical Rules with Adaptive Learning of Structured Information -- Transformation and Explanation -- Lessons from Past, Current Issues, and Future Research Directions in Extracting the Knowledge Embedded in Artificial Neural Networks -- Symbolic Rule Extraction from the DIMLP Neural Network -- Understanding State Space Organization in Recurrent Neural Networks with Iterative Function Systems Dynamics -- Direct Explanations and Knowledge Extraction from a Multilayer Perceptron Network that Performs Low Back Pain Classification -- High Order Eigentensors as Symbolic Rules in Competitive Learning -- Holistic Symbol Processing and the Sequential RAAM: An Evaluation -- Robotics, Vision and Cognitive Approaches -- Life, Mind, and Robots -- Supplementing Neural Reinforcement Learning with Symbolic Methods -- Self-Organizing Maps in Symbol Processing -- Evolution of Symbolisation: Signposts to a Bridge between Connectionist and Symbolic Systems -- A Cellular Neural Associative Array for Symbolic Vision -- Application of Neurosymbolic Integration for Environment Modelling in Mobile Robots. 330 $aHybrid neural systems are computational systems which are based mainly on artificial neural networks and allow for symbolic interpretation or interaction with symbolic components. This book is derived from a workshop held during the NIPS'98 in Denver, Colorado, USA, and competently reflects the state of the art of research and development in hybrid neural systems. The 26 revised full papers presented together with an introductory overview by the volume editors have been through a twofold process of careful reviewing and revision. The papers are organized in the following topical sections: structured connectionism and rule representation; distributed neural architectures and language processing; transformation and explanation; robotics, vision, and cognitive approaches. 410 0$aLecture Notes in Artificial Intelligence ;$v1778 606 $aNeurosciences 606 $aArtificial intelligence 606 $aComputers 606 $aMicroprocessors 606 $aNeurosciences$3https://scigraph.springernature.com/ontologies/product-market-codes/B18006 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputation by Abstract Devices$3https://scigraph.springernature.com/ontologies/product-market-codes/I16013 606 $aProcessor Architectures$3https://scigraph.springernature.com/ontologies/product-market-codes/I13014 615 0$aNeurosciences. 615 0$aArtificial intelligence. 615 0$aComputers. 615 0$aMicroprocessors. 615 14$aNeurosciences. 615 24$aArtificial Intelligence. 615 24$aComputation by Abstract Devices. 615 24$aProcessor Architectures. 676 $a006.3/2 702 $aWermter$b Stefan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSun$b Ron$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910144131803321 996 $aHybrid neural systems$91501903 997 $aUNINA