Librarian View
Last updated in SearchWorks on November 25, 2023 3:12am
LEADER 07574cam a2200637Mu 4500
001
a13013062
003
SIRSI
006
m o d
007
cr |n|---|||||
008
120528s2012 si ob 000 0 eng d
035
a| (Sirsi) a13013062
040
a| EBLCP
b| eng
e| pn
c| EBLCP
d| OCLCQ
d| YDXCP
d| N$T
d| OCLCQ
d| OCLCF
d| OCLCQ
d| OCLCO
d| OCLCQ
d| E7B
d| I9W
d| OCLCQ
d| AGLDB
d| OCLCQ
d| UUM
d| VTS
d| REC
d| OCLCQ
d| AU@
d| OTZ
d| STF
d| M8D
d| UKAHL
d| OCLCQ
019
a| 797852194
a| 1058642735
a| 1086420411
020
a| 9789814360784
q| (electronic bk.)
020
a| 9814360783
q| (electronic bk.)
020
z| 9814360775
020
z| 9789814360777
035
a| (OCoLC)794328422
z| (OCoLC)797852194
z| (OCoLC)1058642735
z| (OCoLC)1086420411
050
4
a| QA76.9 .S63
072
7
a| COM
x| 005030
2| bisacsh
072
7
a| COM
x| 004000
2| bisacsh
082
0
4
a| 006.3
049
a| MAIN
100
1
a| Shi, Zhongzhi.
245
1
0
a| Intelligence Science.
260
a| Singapore :
b| World Scientific,
c| 2012.
300
a| 1 online resource (682 pages)
336
a| text
b| txt
2| rdacontent
337
a| computer
b| c
2| rdamedia
338
a| online resource
b| cr
2| rdacarrier
490
1
a| Series on Intelligence Science
505
0
a| Preface; Acknowledgement; Contents; Chapter 1 Introduction; 1.1 The Dream of Mankind; 1.2 The Rise of Intelligence Science; 1.3 Research Contents; 1.3.1 Basic process of neural activity; 1.3.2 Synaptic plasticity; 1.3.3 Perceptual representation and feature binding; 1.3.4 Coding and retrieval of memory; 1.3.5 Linguistic cognition; 1.3.6 Learning; 1.3.7 Thought; 1.3.8 Emotion; 1.3.9 Nature of consciousness; 1.3.10 Mind modeling; 1.4 Research Methods; 1.4.1 Behavioral experiments; 1.4.2 Brain imaging; 1.4.3 Computational modeling; 1.4.4 Neurobiological methods; 1.4.5 Simulation.
505
8
a| 1.5 Research Roadmap of Intelligence Science1. Short-term goal (2010-2020); 2. Medium-term goal (2020-2035); 3. Long-term goal (2035-2050); Chapter 2 Foundation of Neurophysiology; 2.1 Brain; 2.2 Nervous Tissues; 2.2.1 Basal composition of neuron; 2.2.2 Classification of neurons; 2.2.3 Neuroglial cells; 2.3 Synaptic Transmission; 2.3.1 Chemical synapse; 2.3.2 Electrical synapse; 2.3.3 Mechanism of synaptic transmission; 2.4 Neurotransmitter; 2.4.1 Acetylcholine; 2.4.2 Catecholamines; 2.4.3 5-hydroxytryptamine; 2.4.4 Amine acid and oligopeptide; 2.4.5 Nitric oxide; 2.4.6 Receptor.
505
8
a| 2.5 Transmembrane Signal Transduction2.5.1 Transducin; 2.5.2 The second messenger; 2.6 Resting Membrane Potential; 2.7 Action Potential; 2.8 Ion Channels; 2.9 The Nervous System; 2.9.1 The second messenger; 2.9.2 Peripheral nervous system; 2.10 Cerebral Cortex; Chapter 3 Neural Computation; 3.1 Overview; 3.2 Neuron Model; 3.3 Back-Propagation Learning Algorithm; 3.2.1 Back propagation principle; 3.2.2 Back propagation algorithm; 3.2.4 Advantages and disadvantages of back-propagation network; 3.4 Neural Network Ensemble; 3.4.1 Generation of conclusion; 3.4.2 Generation of individual.
505
8
a| 3.5 Bayesian Linking Field Model3.5.1 Related works; 3.5.2 Noisy neuron firing strategy; 3.5.3 Bayesian coupling of inputs; 3.5.4 Competition among neurons; 3.6 Neural Field Model; 3.7 Nrural Column Model; Chapter 4 Mind Model; 4.1 Introduction; 4.2 The Physical Symbol System; 4.3 ACT-R Model; 4.3.1 Brief history; 4.3.2 The ACT-R architecture; 4.3.3 ACT-R works; (1) Modules; (2) Buffers; (3) Pattern Matcher; 4.3.4 Applications of ACT-R; 4.4 SOAR; 4.5 Society of Mind; 4.6 CAM Model; 4.7 Synergetics; 4.8 Dynamical System Theory; Chapter 5 Perceptual Cognition.
505
8
a| 5.1 Dialectic Process of Understanding5.2 Sensation; 5.3 Perception; 5.4 Combination of Perception; 1. Approaching combination; 2. Similar combination; 3. Combination of the good figure; 5.5 Perception Theories; 5.5.1 Constructing theory; 5.5.2 Gestalt theory; 5.5.3 Movement theory; 5.5.4 Gibson's ecology theory; 5.6 Representation; 1. Intuitivity; 2. Generality; 3. Representation happens on paths of many kinds of feelings; 4. Role of representation in thinking; 5.7 Attention in the Perceptual Cognition; 5.7.1 Filter model; 5.7.2 Decay model; 5.7.3 Response selection model.
500
a| 5.7.4 Energy distribution model.
520
a| Intelligence Science is an interdisciplinary subject dedicated to joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. Brain science explores the essence of brain research on the principle and model of natural intelligence at the molecular, cell and behavior level. Cognitive science studies human mental activity, such as perception, learning, memory, thinking, consciousness etc. In order to implement machine intelligence, artificial intelligence attempts simulation, extension and expansion of human intelligence u.
588
0
a| Print version record.
504
a| Includes bibliographical references.
650
0
a| Artificial intelligence.
650
7
a| COMPUTERS
x| Enterprise Applications
x| Business Intelligence Tools.
2| bisacsh
650
7
a| COMPUTERS
x| Intelligence (AI) & Semantics.
2| bisacsh
650
7
a| Artificial intelligence.
2| fast
0| (OCoLC)fst00817247
776
0
8
i| Print version:
a| Shi, Zhongzhi.
t| Intelligence Science.
d| Singapore : World Scientific, ©2012
z| 9789814360777
830
0
a| Series on intelligence science.
856
4
0
z| Available to Stanford-affiliated users.
u| http://search.ebscohost.com/login.aspx?authtype=ip,sso&custid=s4392798&direct=true&scope=site&db=nlebk&AN=457235
x| WMS
y| EBSCO Academic Comprehensive Collection
x| Provider: EBSCO
x| subscribed
x| eLoaderURL
x| uc4
x| ucocn794328422
994
a| 92
b| STF
905
0
a| Introduction-- Foundation of Neuro-Physiology-- Neural Computing-- Mind Model-- Perception-- Visual Information Processing-- Audio Information Processing-- Language-- Learning-- Memory-- Thought-- Development of Intelligence-- Emotion-- Immune System-- Consciousness-- Symbolic Logic-- The Machine Proves-- Perspective.
1| Nielsen
x| 9789814360777
x| 20190128
920
b| Intelligence Science is an interdisciplinary subject dedicated to joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. Brain science explores the essence of brain research on the principle and model of natural intelligence at the molecular, cell and behavior level. Cognitive science studies human mental activity, such as perception, learning, memory, thinking, consciousness etc. In order to implement machine intelligence, artificial intelligence attempts simulation, extension and expansion of human intelligence using artificial methodology and technology. Research scientists from the above three disciplines work together to explore new concepts, new theories, and methodologies.This book will introduce the concept and methodology of intelligence science systematically. The whole book is divided into 18 chapters altogether. It can be regarded as a textbook in courses of intelligence science, cognitive science, cognitive informatics etc. for senior and graduate students. It has important reference value for researchers engaged in fields such as intelligence science, brain science, cognitive science, neural science, artificial intelligence, psychology and so on.
1| Nielsen
x| 9789814360777
x| 20190128
915
a| NO EXPORT
b| AUTHORITY VENDOR
d| 20190128
596
a| 22
035
a| (Sirsi) ucocn794328422
999
f
f
i| 7a18eeac-9da7-5355-81d5-f4f228a6b98d
s| 015532b3-3f16-53e7-81bb-46c187a1e5d0
Holdings JSON
{ "holdings": [ { "id": "4623949b-1e92-509b-90ed-2e853ff859b5", "hrid": "ah13013062_1", "notes": [ ], "_version": 1, "metadata": { "createdDate": "2023-08-21T19:23:08.208Z", "updatedDate": "2023-08-21T19:23:08.208Z", "createdByUserId": "58d0aaf6-dcda-4d5e-92da-012e6b7dd766", "updatedByUserId": "58d0aaf6-dcda-4d5e-92da-012e6b7dd766" }, "sourceId": "f32d531e-df79-46b3-8932-cdd35f7a2264", "boundWith": null, "formerIds": [ ], "illPolicy": null, "instanceId": "7a18eeac-9da7-5355-81d5-f4f228a6b98d", "holdingsType": { "id": "996f93e2-5b5e-4cf2-9168-33ced1f95eed", "name": "Electronic", "source": "folio" }, "holdingsItems": [ ], "callNumberType": null, "holdingsTypeId": "996f93e2-5b5e-4cf2-9168-33ced1f95eed", "electronicAccess": [ ], "bareHoldingsItems": [ ], "holdingsStatements": [ ], "statisticalCodeIds": [ ], "administrativeNotes": [ ], "effectiveLocationId": "b0a1a8c3-cc9a-487c-a2ed-308fc3a49a91", "permanentLocationId": "b0a1a8c3-cc9a-487c-a2ed-308fc3a49a91", "suppressFromDiscovery": false, "holdingsStatementsForIndexes": [ ], "holdingsStatementsForSupplements": [ ], "location": { "effectiveLocation": { "id": "b0a1a8c3-cc9a-487c-a2ed-308fc3a49a91", "code": "SUL-ELECTRONIC", "name": "online resource", "campus": { "id": "c365047a-51f2-45ce-8601-e421ca3615c5", "code": "SUL", "name": "Stanford Libraries" }, "details": { }, "library": { "id": "c1a86906-ced0-46cb-8f5b-8cef542bdd00", "code": "SUL", "name": "SUL" }, "isActive": true, "institution": { "id": "8d433cdd-4e8f-4dc1-aa24-8a4ddb7dc929", "code": "SU", "name": "Stanford University" } }, "permanentLocation": { "id": "b0a1a8c3-cc9a-487c-a2ed-308fc3a49a91", "code": "SUL-ELECTRONIC", "name": "online resource", "campus": { "id": "c365047a-51f2-45ce-8601-e421ca3615c5", "code": "SUL", "name": "Stanford Libraries" }, "details": { }, "library": { "id": "c1a86906-ced0-46cb-8f5b-8cef542bdd00", "code": "SUL", "name": "SUL" }, "isActive": true, "institution": { "id": "8d433cdd-4e8f-4dc1-aa24-8a4ddb7dc929", "code": "SU", "name": "Stanford University" } } } } ], "items": [ ] }
FOLIO JSON
{ "pieces": [ null ], "instance": { "id": "7a18eeac-9da7-5355-81d5-f4f228a6b98d", "hrid": "a13013062", "notes": [ { "note": "Preface; Acknowledgement; Contents; Chapter 1 Introduction; 1.1 The Dream of Mankind; 1.2 The Rise of Intelligence Science; 1.3 Research Contents; 1.3.1 Basic process of neural activity; 1.3.2 Synaptic plasticity; 1.3.3 Perceptual representation and feature binding; 1.3.4 Coding and retrieval of memory; 1.3.5 Linguistic cognition; 1.3.6 Learning; 1.3.7 Thought; 1.3.8 Emotion; 1.3.9 Nature of consciousness; 1.3.10 Mind modeling; 1.4 Research Methods; 1.4.1 Behavioral experiments; 1.4.2 Brain imaging; 1.4.3 Computational modeling; 1.4.4 Neurobiological methods; 1.4.5 Simulation", "staffOnly": false, "instanceNoteTypeId": "5ba8e385-0e27-462e-a571-ffa1fa34ea54" }, { "note": "1.5 Research Roadmap of Intelligence Science1. Short-term goal (2010-2020); 2. Medium-term goal (2020-2035); 3. Long-term goal (2035-2050); Chapter 2 Foundation of Neurophysiology; 2.1 Brain; 2.2 Nervous Tissues; 2.2.1 Basal composition of neuron; 2.2.2 Classification of neurons; 2.2.3 Neuroglial cells; 2.3 Synaptic Transmission; 2.3.1 Chemical synapse; 2.3.2 Electrical synapse; 2.3.3 Mechanism of synaptic transmission; 2.4 Neurotransmitter; 2.4.1 Acetylcholine; 2.4.2 Catecholamines; 2.4.3 5-hydroxytryptamine; 2.4.4 Amine acid and oligopeptide; 2.4.5 Nitric oxide; 2.4.6 Receptor", "staffOnly": false, "instanceNoteTypeId": "5ba8e385-0e27-462e-a571-ffa1fa34ea54" }, { "note": "2.5 Transmembrane Signal Transduction2.5.1 Transducin; 2.5.2 The second messenger; 2.6 Resting Membrane Potential; 2.7 Action Potential; 2.8 Ion Channels; 2.9 The Nervous System; 2.9.1 The second messenger; 2.9.2 Peripheral nervous system; 2.10 Cerebral Cortex; Chapter 3 Neural Computation; 3.1 Overview; 3.2 Neuron Model; 3.3 Back-Propagation Learning Algorithm; 3.2.1 Back propagation principle; 3.2.2 Back propagation algorithm; 3.2.4 Advantages and disadvantages of back-propagation network; 3.4 Neural Network Ensemble; 3.4.1 Generation of conclusion; 3.4.2 Generation of individual", "staffOnly": false, "instanceNoteTypeId": "5ba8e385-0e27-462e-a571-ffa1fa34ea54" }, { "note": "3.5 Bayesian Linking Field Model3.5.1 Related works; 3.5.2 Noisy neuron firing strategy; 3.5.3 Bayesian coupling of inputs; 3.5.4 Competition among neurons; 3.6 Neural Field Model; 3.7 Nrural Column Model; Chapter 4 Mind Model; 4.1 Introduction; 4.2 The Physical Symbol System; 4.3 ACT-R Model; 4.3.1 Brief history; 4.3.2 The ACT-R architecture; 4.3.3 ACT-R works; (1) Modules; (2) Buffers; (3) Pattern Matcher; 4.3.4 Applications of ACT-R; 4.4 SOAR; 4.5 Society of Mind; 4.6 CAM Model; 4.7 Synergetics; 4.8 Dynamical System Theory; Chapter 5 Perceptual Cognition", "staffOnly": false, "instanceNoteTypeId": "5ba8e385-0e27-462e-a571-ffa1fa34ea54" }, { "note": "5.1 Dialectic Process of Understanding5.2 Sensation; 5.3 Perception; 5.4 Combination of Perception; 1. Approaching combination; 2. Similar combination; 3. Combination of the good figure; 5.5 Perception Theories; 5.5.1 Constructing theory; 5.5.2 Gestalt theory; 5.5.3 Movement theory; 5.5.4 Gibson's ecology theory; 5.6 Representation; 1. Intuitivity; 2. Generality; 3. Representation happens on paths of many kinds of feelings; 4. Role of representation in thinking; 5.7 Attention in the Perceptual Cognition; 5.7.1 Filter model; 5.7.2 Decay model; 5.7.3 Response selection model", "staffOnly": false, "instanceNoteTypeId": "5ba8e385-0e27-462e-a571-ffa1fa34ea54" }, { "note": "5.7.4 Energy distribution model", "staffOnly": false, "instanceNoteTypeId": "6a2533a7-4de2-4e64-8466-074c2fa9308c" }, { "note": "Intelligence Science is an interdisciplinary subject dedicated to joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. Brain science explores the essence of brain research on the principle and model of natural intelligence at the molecular, cell and behavior level. Cognitive science studies human mental activity, such as perception, learning, memory, thinking, consciousness etc. In order to implement machine intelligence, artificial intelligence attempts simulation, extension and expansion of human intelligence u", "staffOnly": false, "instanceNoteTypeId": "10e2e11b-450f-45c8-b09b-0f819999966e" }, { "note": "Print version record", "staffOnly": false, "instanceNoteTypeId": "66ea8f28-d5da-426a-a7c9-739a5d676347" }, { "note": "Includes bibliographical references", "staffOnly": false, "instanceNoteTypeId": "86b6e817-e1bc-42fb-bab0-70e7547de6c1" } ], "title": "Intelligence Science.", "series": [ "Series on Intelligence Science", "Series on intelligence science" ], "source": "MARC", "_version": 1, "editions": [ ], "metadata": { "createdDate": "2023-08-21T19:21:37.204Z", "updatedDate": "2023-08-21T19:21:37.204Z", "createdByUserId": "58d0aaf6-dcda-4d5e-92da-012e6b7dd766", "updatedByUserId": "58d0aaf6-dcda-4d5e-92da-012e6b7dd766" }, "statusId": "9634a5ab-9228-4703-baf2-4d12ebc77d56", "subjects": [ "Artificial intelligence", "COMPUTERS Enterprise Applications Business Intelligence Tools", "COMPUTERS Intelligence (AI) & Semantics" ], "languages": [ "eng" ], "indexTitle": "Intelligence science.", "identifiers": [ { "value": "(Sirsi) a13013062", "identifierTypeId": "7e591197-f335-4afb-bc6d-a6d76ca3bace" }, { "value": "9789814360784 (electronic bk.)", "identifierTypeId": "8261054f-be78-422d-bd51-4ed9f33c3422" }, { "value": "9814360783 (electronic bk.)", "identifierTypeId": "8261054f-be78-422d-bd51-4ed9f33c3422" }, { "value": "9814360775", "identifierTypeId": "fcca2643-406a-482a-b760-7a7f8aec640e" }, { "value": "9789814360777", "identifierTypeId": "fcca2643-406a-482a-b760-7a7f8aec640e" }, { "value": "(OCoLC)794328422", "identifierTypeId": "439bfbae-75bc-4f74-9fc7-b2a2d47ce3ef" }, { "value": "(OCoLC)797852194", "identifierTypeId": "fc4e3f2a-887a-46e5-8057-aeeb271a4e56" }, { "value": "(OCoLC)1058642735", "identifierTypeId": "fc4e3f2a-887a-46e5-8057-aeeb271a4e56" }, { "value": "(OCoLC)1086420411", "identifierTypeId": "fc4e3f2a-887a-46e5-8057-aeeb271a4e56" }, { "value": "(Sirsi) ucocn794328422", "identifierTypeId": "7e591197-f335-4afb-bc6d-a6d76ca3bace" } ], "publication": [ { "place": "Singapore", "publisher": "World Scientific", "dateOfPublication": "2012" } ], "contributors": [ { "name": "Shi, Zhongzhi", "primary": true, "contributorTypeId": "9f0a2cf0-7a9b-45a2-a403-f68d2850d07c", "contributorNameTypeId": "2b94c631-fca9-4892-a730-03ee529ffe2a" } ], "catalogedDate": "2019-01-24", "staffSuppress": false, "instanceTypeId": "6312d172-f0cf-40f6-b27d-9fa8feaf332f", "previouslyHeld": false, "classifications": [ { "classificationNumber": "QA76.9 .S63", "classificationTypeId": "ce176ace-a53e-4b4d-aa89-725ed7b2edac" }, { "classificationNumber": "006.3", "classificationTypeId": "42471af9-7d25-4f3a-bf78-60d29dcf463b" } ], "instanceFormats": [ ], "electronicAccess": [ { "uri": "http://search.ebscohost.com/login.aspx?authtype=ip,sso&custid=s4392798&direct=true&scope=site&db=nlebk&AN=457235", "name": "Resource", "linkText": "EBSCO Academic Comprehensive Collection", "publicNote": "Available to Stanford-affiliated users", "relationshipId": "f5d0068e-6272-458e-8a81-b85e7b9a14aa" } ], "holdingsRecords2": [ ], "modeOfIssuanceId": "9d18a02f-5897-4c31-9106-c9abb5c7ae8b", "publicationRange": [ ], "statisticalCodes": [ ], "alternativeTitles": [ ], "discoverySuppress": false, "instanceFormatIds": [ "f5e8210f-7640-459b-a71f-552567f92369" ], "publicationPeriod": { "start": 2012 }, "statusUpdatedDate": "2023-08-21T19:21:37.191+0000", "statisticalCodeIds": [ ], "administrativeNotes": [ ], "physicalDescriptions": [ "1 online resource (682 pages)" ], "publicationFrequency": [ ], "suppressFromDiscovery": false, "natureOfContentTermIds": [ ] }, "holdingSummaries": [ { "poLineId": null, "orderType": null, "orderStatus": null, "poLineNumber": null, "orderSentDate": null, "orderCloseReason": null, "polReceiptStatus": null } ] }