LEADER 04623nam 22006255 450 001 996465834903316 005 20200702014356.0 010 $a3-540-44565-X 024 7 $a10.1007/3-540-44565-X 035 $a(CKB)1000000000211254 035 $a(SSID)ssj0000326625 035 $a(PQKBManifestationID)11255962 035 $a(PQKBTitleCode)TC0000326625 035 $a(PQKBWorkID)10297042 035 $a(PQKB)11775179 035 $a(DE-He213)978-3-540-44565-4 035 $a(MiAaPQ)EBC3072729 035 $a(PPN)155226657 035 $a(EXLCZ)991000000000211254 100 $a20121227d2001 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aSequence Learning$b[electronic resource] $eParadigms, Algorithms, and Applications /$fedited by Ron Sun, C.Lee Giles 205 $a1st ed. 2001. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2001. 215 $a1 online resource (XII, 396 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v1828 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-41597-1 320 $aIncludes bibliographical references and index. 327 $ato Sequence Learning -- to Sequence Learning -- Sequence Clustering and Learning with Markov Models -- Sequence Learning via Bayesian Clustering by Dynamics -- Using Dynamic Time Warping to Bootstrap HMM-Based Clustering of Time Series -- Sequence Prediction and Recognition with Neural Networks -- Anticipation Model for Sequential Learning of Complex Sequences -- Bidirectional Dynamics for Protein Secondary Structure Prediction -- Time in Connectionist Models -- On the Need for a Neural Abstract Machine -- Sequence Discovery with Symbolic Methods -- Sequence Mining in Categorical Domains: Algorithms and Applications -- Sequence Learning in the ACT-R Cognitive Architecture: Empirical Analysis of a Hybrid Model -- Sequential Decision Making -- Sequential Decision Making Based on Direct Search -- Automatic Segmentation of Sequences through Hierarchical Reinforcement Learning -- Hidden-Mode Markov Decision Processes for Nonstationary Sequential Decision Making -- Pricing in Agent Economies Using Neural Networks and Multi-agent Q-Learning -- Biologically Inspired Sequence Learning Models -- Multiple Forward Model Architecture for Sequence Processing -- Integration of Biologically Inspired Temporal Mechanisms into a Cortical Framework for Sequence Processing -- Attentive Learning of Sequential Handwriting Movements: A Neural Network Model. 330 $aSequential behavior is essential to intelligence in general and a fundamental part of human activities, ranging from reasoning to language, and from everyday skills to complex problem solving. Sequence learning is an important component of learning in many tasks and application fields: planning, reasoning, robotics natural language processing, speech recognition, adaptive control, time series prediction, financial engineering, DNA sequencing, and so on. This book presents coherently integrated chapters by leading authorities and assesses the state of the art in sequence learning by introducing essential models and algorithms and by examining a variety of applications. The book offers topical sections on sequence clustering and learning with Markov models, sequence prediction and recognition with neural networks, sequence discovery with symbolic methods, sequential decision making, biologically inspired sequence learning models. 410 0$aLecture Notes in Artificial Intelligence ;$v1828 606 $aArtificial intelligence 606 $aComputers 606 $aAlgorithms 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 $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021 615 0$aArtificial intelligence. 615 0$aComputers. 615 0$aAlgorithms. 615 14$aArtificial Intelligence. 615 24$aComputation by Abstract Devices. 615 24$aAlgorithm Analysis and Problem Complexity. 676 $a006.3/1 702 $aSun$b Ron$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGiles$b C.Lee$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a996465834903316 996 $aSequence Learning$9378166 997 $aUNISA