Cohen / Lefebvre Handbook of Categorization in Cognitive Science

1. Auflage 2005
ISBN: 978-0-08-045741-3
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 1136 Seiten

Categorization, the basic cognitive process of arranging objects into categories, is a fundamental process in human and machine intelligence and is central to investigations and research in cognitive science. Until now, categorization has been approached from singular disciplinary perspectives with little overlap or communication between the disciplines involved (Linguistics, Psychology, Philosophy, Neuroscience, Computer Science, Cognitive Anthropology). Henri Cohen and Claire Lefebvre have gathered together a stellar collection of contributors in this unique, ambitious attempt to bring together converging disciplinary and conceptual perspectives on this topic.
'Categorization is a key concept across the range of cognitive sciences, including linguistics and philosophy, yet hitherto it has been hard to find accounts that go beyond the concerns of one or two individual disciplines. The Handbook of Categorization in Cognitive Science provides just the sort of interdisciplinary approach that is necessary to synthesize knowledge from the different fields and provide the basis for future innovation.'
Professor Bernard Comrie, Department of Linguistics, Max Planck Institute for Evolutionary Anthropology, Germany
'Anyone concerned with language, semantics, or categorization will want to have this encyclopedic collection.'
Professor Eleanor Rosch, Dept of Psychology, University of California, Berkeley, USA

Autoren/Hrsg.

Cohen, Henri

Lefebvre, Claire

Inhaltsverzeichnis

1;Cover;1
2;Handbook of Categorization in Cognitive Science;4
3;Preface;6
4;Table of Contents;8
5;List of Contributors;30
6;Bridging the Category Divide;38
6.1;Introduction;39
6.2;Organization of the book;39
6.3;Major common themes;44
6.3.1;The notions of category and categorization;44
6.3.2;The nature of categories: Discrete, vague, or other;46
6.3.3;Are there modality effects on categories?;47
6.3.4;Are there universal categories? Are there innate categories?;48
6.4;Bridging the category divide;50
6.5;References;52
7;Part 1 – Categorization in Cognitive Science;54
7.1;To Cognize is to Categorize: Cognition is Categorization;56
7.1.1;Abstract;57
7.1.2;Sensorimotor systems;58
7.1.3;Invariant sensorimotor features (“affordances”);58
7.1.4;Categorization;58
7.1.5;Learning;59
7.1.6;Innate categories;60
7.1.7;Learned categories;60
7.1.8;Supervised learning;61
7.1.9;Instrumental (operant) learning;61
7.1.10;Color categories;62
7.1.11;Categorical perception;62
7.1.12;Learning algorithms;63
7.1.13;Unsupervised learning;64
7.1.14;Supervised learning;64
7.1.15;Vanishing intersections?;65
7.1.16;Direct sensorimotor invariants;66
7.1.17;Abstraction and hearsay;67
7.1.18;Abstraction and amnesia;67
7.1.19;Invariance and recurrence;68
7.1.20;Feature selection and weighting;69
7.1.21;Discrimination versus categorization;69
7.1.22;Recoding and feature selection;70
7.1.23;Learned categorical perception and the Whorf hypothesis;71
7.1.24;Uncertainty reduction;72
7.1.25;Explicit learning;73
7.1.26;Categorization is abstraction;73
7.1.27;Sensorimotor grounding: direct and derivative;73
7.1.28;The adaptive advantage of language: hearsay;74
7.1.29;Absolute discriminables and affordances;76
7.1.30;Cognitive science is not ontology;76
7.1.31;Cognition is categorization;77
7.1.32;Appendix A. There is nothing wrong with the “classical theory” of categorization;77
7.1.33;Appendix B. Associationism begs the question of categorization;78
7.1.34;References;79
7.2;A Modular Approach to Grammatical Categories Evidence from Language Diversity and Contact;82
7.2.1;Abstract;83
7.2.2;Introduction;84
7.2.3;Modularity and mismatch;85
7.2.4;Grammaticalization: The case of pe in Sranan (Suriname);89
7.2.5;Mismatches in complexity of representations: The case of ku in Cuzco Quechua (Peru);91
7.2.6;Lexical nondistinctness;92
7.2.6.1;The case of timap in Palikur;92
7.2.6.2;‘For’ prepositions to become complementizers;93
7.2.6.3;Adjectives versus adverbs;94
7.2.7;Lexical overspecification: Dutch gender and definiteness;94
7.2.8;The status of null elements: Subjects in Sranan and Papiamentu;95
7.2.9;Partially overlapping categories: predicate adjectives in Creoles;96
7.2.10;Differences in lexical richness;97
7.2.11;Evidence from language contact;98
7.2.11.1;Otomanguean-Spanish language contact;99
7.2.11.2;Borrowing of content words in Salishan languages;102
7.2.12;Concluding remarks;104
7.2.13;Appendix;104
7.2.14;References;105
7.3;Philosophical Analysis as Cognitive Psychology: The Case of Empty Concepts*;108
7.3.1;Abstract;109
7.3.2;Introduction;110
7.3.3;Misadventures of the Classical View;110
7.3.4;Terminological issues;112
7.3.4.1;Existential vs. (purely) intentional usage;112
7.3.4.2;Concepts as between representations and referents;114
7.3.5;The inadequacies of Externalism;114
7.3.6;The need for internal roles;119
7.3.6.1;The Quinean challenge;119
7.3.6.2;The analytic data;120
7.3.6.3;Rivals to the Analytic Explanation;122
7.3.6.3.1;Quine;122
7.3.6.3.2;Fodor;123
7.3.7;Conclusion;124
7.3.8;References;125
7.4;Categories and Cognitive Anthropology*;128
7.4.1;Abstract;129
7.4.2;Introduction;130
7.4.3;Cognition and culture, universalism and relativism;130
7.4.4;Paradigms and taxonomies;131
7.4.5;Kinship terminologies;138
7.4.6;Color classification;142
7.4.7;Ethnobiology;146
7.4.8;Towards a science of the stimulus;151
7.4.9;References;153
7.5;Categorization in Neuroscience: Brain Response to Objects and Events;156
7.5.1;Abstract;156
7.5.2;Introduction;157
7.5.3;Representing object categories in the brain;158
7.5.4;Category-specific representation;159
7.5.5;Feature-specific representation;160
7.5.6;Process-specific representation;162
7.5.7;Summary;162
7.5.8;Acquiring category knowledge;163
7.5.9;Summary;167
7.5.10;Categorizing actions and events;167
7.5.11;The nature of event knowledge;167
7.5.12;When categorization of action fails;169
7.5.13;The perception of events;170
7.5.14;Summary;173
7.5.15;Conclusion;173
7.5.16;References;174
7.6;Categorization in Cognitive Computer Science;178
7.6.1;Abstract;178
7.6.2;Computation in cognitive science;179
7.6.3;The great categorization debates;181
7.6.4;From local features to global structures;185
7.6.5;Categorization and reasoning;190
7.6.6;Levels of cognition;195
7.6.7;References;198
8;Part 2 – Semantic Categories;202
8.1;Semantic Categorization;204
8.1.1;Abstract;204
8.1.2;Introduction;205
8.1.3;The notional approach to lexical categories;206
8.1.4;The notional approach to lexical subcategories;207
8.1.5;Structural approach to semantic categories;209
8.1.6;Coordinators and subordinators;212
8.1.7;English nouns;218
8.1.8;Conclusion;221
8.1.9;Acknowledgments;221
8.1.10;References;221
8.2;Emotion Categories across Languages;224
8.2.1;Abstract;225
8.2.2;Introduction;226
8.2.3;Methods of assessing cultural emotion systems;228
8.2.3.1;The Method of Translation;228
8.2.3.2;The Method of Mapping;235
8.2.4;Theories of emotion;247
8.2.5;Cross-cultural scenarios as a tool to compare emotion categories;250
8.2.6;Conclusion;255
8.2.7;References;257
8.3;The World Color Survey Database;260
8.3.1;Abstract;261
8.3.2;Introduction;262
8.3.3;The WCS: History and methodology;262
8.3.4;Data processing and analysis;265
8.3.5;Cleaning the data;269
8.3.6;Original format of the data and creation of the WCS Online Data Archive;269
8.3.7;Uses of the WCS archive;271
8.3.7.1;Universals of color naming;271
8.3.7.2;Variation in color naming;274
8.3.8;Conclusion;277
8.3.9;References;277
8.4;Atoms, Categorization and Conceptual Change;280
8.4.1;Abstract;280
8.4.2;Introduction;281
8.4.3;Theories of concepts;282
8.4.4;The ancient concept of an atom;283
8.4.5;Revival of the concept of the atom;285
8.4.6;Modern development of the concept of an atom;286
8.4.7;Theories and meaning;289
8.4.8;Conclusion;290
8.4.9;References;290
8.5;Relations between Language and Thought: Individuation and the Count/Mass Distinction*;292
8.5.1;Abstract;293
8.5.2;Introduction;294
8.5.3;Strong discontinuity proposals;297
8.5.3.1;Quine;297
8.5.3.2;Abstract individuation in language and thought;299
8.5.4;Weak discontinuity proposals;300
8.5.4.1;Crosslinguistic studies;300
8.5.4.2;Language-on-language effects;303
8.5.5;Material and shape cues in labeling and categorization;305
8.5.6;Conclusion;308
8.5.7;References;308
8.6;Definitions in Categorization and Similarity Judgments;314
8.6.1;Abstract;315
8.6.2;Introduction;316
8.6.3;Importance rating and property selection;321
8.6.3.1;Method;321
8.6.3.2;Results;323
8.6.4;Categorization judgments;325
8.6.4.1;Method;325
8.6.4.2;Results;327
8.6.4.3;Discussion;333
8.6.5;Similarity judgments;334
8.6.5.1;Method;334
8.6.5.2;Results;335
8.6.6;General discussion;337
8.6.7;References;339
8.7;Why (Most) Concepts aren’t Categories;342
8.7.1;Abstract;342
8.7.2;Introduction;343
8.7.3;Species are not categories;343
8.7.4;Three kinds of (Aristotelian) “substances”;344
8.7.4.1;Historical kinds;344
8.7.4.2;Eternal kinds;345
8.7.4.3;Individuals;346
8.7.5;Concepts of individuals;347
8.7.6;Concepts of substances more generally;348
8.7.7;Substances encountered through language;349
8.7.8;References;352
9;Part 3 – Syntactic Categories;354
9.1;Lexical, Functional, Crossover, and Multifunctional Categories*;356
9.1.1;Abstract;357
9.1.2;Introduction;358
9.1.3;Categories as feature bundles;358
9.1.3.1;The system;358
9.1.3.2;Natural classes;359
9.1.3.3;Unnatural classes;361
9.1.4;Categories and phrase structure;362
9.1.4.1;Lexical and functional categories;363
9.1.4.2;Articulation of functional categories;364
9.1.4.3;Articulation below N and V;366
9.1.4.4;Crossover and multifunctionality;367
9.1.4.4.1;Crossover projections;367
9.1.4.4.2;Multifunctional categories;372
9.1.5;Where do categorial distinctions reside?;373
9.1.6;Conclusions;381
9.1.7;References;382
9.2;Isolating-Monocategorial-Associational Language;384
9.2.1;Abstract;385
9.2.2;Introduction;386
9.2.3;What IMA Language is Like;386
9.2.3.1;Isolating;387
9.2.3.2;Monocategorial;387
9.2.3.3;Associational;388
9.2.4;Where IMA Language Is Found;391
9.2.4.1;Semiotics;391
9.2.4.2;Phylogeny;393
9.2.4.3;Ontogeny;395
9.2.5;Typology;396
9.2.5.1;Riau Indonesian: overview;397
9.2.5.2;Riau Indonesian: analysis;401
9.2.5.3;Riau Indonesian: A Relative IMA Language;411
9.2.6;Cognition;412
9.2.7;Acknowledgments;414
9.2.8;References;414
9.3;Categories in Quebec Sign Language: Reflections on Categorization across Modalities;418
9.3.1;Abstract;418
9.3.2;The categories of lexical items;419
9.3.3;Traditional categorization applied to LSQ;421
9.3.3.1;Nouns and verbs;424
9.3.3.2;Pronouns and definite determiners;424
9.3.4;Pronouns in oral languages and in sign languages;425
9.3.4.1;The effects of perceptual substances on linguistic forms;426
9.3.4.2;Explaining the different properties;427
9.3.4.2.1;Participant deixis;427
9.3.4.2.2;Inclusion/exclusion of the speaker or hearer;428
9.3.4.2.3;Spatial deixis: proximity, distance, visibility (for third person);428
9.3.4.2.4;Number;428
9.3.4.2.5;Class/gender;430
9.3.4.2.6;Case markings;431
9.3.4.2.7;Summary;433
9.3.5;Consequences for linguistic categorization and universals;433
9.3.6;References;435
9.4;Syntactic Categories in Signed versus Spoken Languages;438
9.4.1;Abstract;439
9.4.2;Introduction;440
9.4.3;Lexical categories;440
9.4.4;Grammatical structures;442
9.4.4.1;Subordination;442
9.4.4.2;“Spatial syntax”;443
9.4.4.2.1;Pronouns;443
9.4.4.2.2;Verb agreement;445
9.4.4.2.3;Analyses of spatial syntax;446
9.4.4.2.4;Complications;448
9.4.4.2.5;The use of space to represent space;449
9.4.4.3;Word order;450
9.4.5;Conclusion;454
9.4.6;Acknowledgments;455
9.4.7;Appendix. Notational conventions;455
9.4.8;References;456
9.5;On Syntactic Categories;460
9.5.1;References;467
10;Part 4 – Acquisition of Categories;468
10.1;The Acquisition of Grammatical Categories: the State of the Art;470
10.1.1;Abstract;470
10.1.2;Grammatical categories;471
10.1.3;Two-word utterances and their analysis;472
10.1.4;A semantic approach to grammatical categorization: Semantic bootstrapping;473
10.1.5;Distributional learning;476
10.1.5.1;Word order;476
10.1.5.2;Inflection and inflectional class;478
10.1.5.3;Function words;482
10.1.5.4;Word classes;484
10.1.5.5;Other cues to grammatical category learning;486
10.1.6;Models of distributional learning;486
10.1.7;Constraining the search space;487
10.1.8;Conclusion;488
10.1.9;References;489
10.2;Semantic Categories in Acquisition;496
10.2.1;Abstract;496
10.2.2;Introduction;497
10.2.3;Space;498
10.2.4;Shape;502
10.2.5;Adding common ground;503
10.2.6;Conceptual domains and lexical options;504
10.2.7;Adding meaning in the course of conversation;509
10.2.8;Universals in mapping?;510
10.2.9;Conclusion;513
10.2.10;References;514
10.3;Early Syntactic Categories in Infants' Language;518
10.3.1;Abstract;518
10.3.2;Introduction;519
10.3.3;The acquisition of grammatical categories and the earliest binary distinction of function words and content words;519
10.3.4;Input speech and the categorization of function words and content words;523
10.3.5;Function words and language acquisition;525
10.3.6;Conclusions;529
10.3.7;Acknowledgment;529
10.3.8;References;530
10.4;Acquiring Auditory and Phonetic Categories*;534
10.4.1;Abstract;534
10.4.2;Introduction;535
10.4.3;Testing category learning;537
10.4.4;Learning of nonspeech categories;539
10.4.5;Learning of speech categories;543
10.4.6;Conclusion;547
10.4.7;References;548
10.5;Syntactic Categories in Second Language Acquisition;552
10.5.1;Abstract;552
10.5.2;Introduction;553
10.5.3;Lexical and functional categories;553
10.5.4;Lexical categories in L2 acquisition;554
10.5.5;Functional categories in acquisition: Issues of evidence;556
10.5.6;Functional categories in the L2 initial state and in L2 development;559
10.5.6.1;Morphology-before-syntax;559
10.5.6.2;Syntax-before-morphology;560
10.5.7;Acquiring versus losing categories and features;561
10.5.8;Discussion;566
10.5.9;References;567
10.6;The Development of Categories in the Linguistic and Nonlinguistic Domains: the Same or Different?;572
10.6.1;References;578
11;Part 5 – Neuroscience of Categorization and Category Learning;582
11.1;Multiple Systems of Perceptual Category Learning: Theory and Cognitive Tests;584
11.1.1;Abstract;585
11.1.2;Introduction;586
11.1.3;Two Category-Learning Tasks;587
11.1.4;COVIS;587
11.1.5;The COVIS explicit system;589
11.1.5.1;Switching attention in the explicit system;591
11.1.5.2;Long-term storage of explicit category knowledge;593
11.1.6;The COVIS procedural-learning system;594
11.1.7;Competition between the COVIS explicit and implicit systems;597
11.1.8;Dissociations between rule-based and information-integration category learning;598
11.1.9;Conclusions;600
11.1.10;Appendix A;601
11.1.10.1;A 1 Network implementation of the explicit system;601
11.1.10.2;A 2 Network implementation of the implicit system;603
11.1.11;Acknowledgment;605
11.1.12;References;605
11.2;The Neuropsychology of Perceptual Category Learning*;610
11.2.1;Abstract;611
11.2.2;Introduction;612
11.2.3;Competition between verbal and implicit systems (COVIS);612
11.2.4;Testing a priori Predictions of COVIS;615
11.2.5;Perceptual category learning in neurological patients;618
11.2.5.1;Nonlinear information-integration category learning in amnesia;619
11.2.5.1.1;Model-based analyses;621
11.2.5.2;Nonlinear information-integration category learning in striatal-damaged patients;622
11.2.5.3;Rule-based category learning in PD;624
11.2.5.4;Further study of information-integration category learning in PD;628
11.2.5.4.1;Brief summary of the results;630
11.2.6;General discussion;632
11.2.7;References;634
11.3;Neural Regions Associated with Categorical Speech Perception and Production;638
11.3.1;Abstract;638
11.3.2;Introduction;639
11.3.3;Evidence for categorical speech processing;639
11.3.4;Prefrontal regions and motor speech categories;642
11.3.5;Temporal–parietal regions and acoustic speech categories;646
11.3.6;Cerebellar contributions to categorical production and perception;648
11.3.7;Concluding remarks;649
11.3.8;References;650
12;Part 6 – Categories in Perception and Inference;654
12.1;Situated Conceptualization;656
12.1.1;Abstract;657
12.1.2;Introduction;658
12.1.2.1;Conceptual systems;658
12.1.2.2;Semantic memory;658
12.1.3;Grounding the conceptual system in the modalities;659
12.1.3.1;Modal reenactments of perception, action, and introspection;660
12.1.3.1.1;Storage of modality-specific states that arise in feature systems;660
12.1.3.1.2;Reenactments of modality-specific states;660
12.1.3.2;Simulators and simulations;661
12.1.3.2.1;Simulators;661
12.1.3.2.2;Simulations;662
12.1.3.2.3;Sources of simulators;662
12.1.3.3;Situated conceptualizations;663
12.1.3.3.1;Multimodal simulations implement situated conceptualizations;663
12.1.3.3.2;Entrenched situated conceptualizations;664
12.1.3.4;Inference via pattern completion;665
12.1.3.4.1;Pattern completion with entrenched situated conceptualizations;665
12.1.3.4.2;The statistical character of inference;666
12.1.4;Empirical evidence;666
12.1.4.1;Behavioral evidence for a modal nonmodular conceptual system;666
12.1.4.1.1;Predictions for modular amodal vs. nonmodular modal theories;667
12.1.4.1.2;Assessing the presence of modality-specific effects in conceptual processing;668
12.1.4.1.3;Occlusion during property generation;668
12.1.4.1.4;Size during property verification;669
12.1.4.1.5;Shape during property verification;670
12.1.4.1.6;Modality switching during property verification;671
12.1.4.1.7;Shape and orientation during comprehension;672
12.1.4.1.8;Movement direction in comprehension;672
12.1.4.1.9;Further evidence for simulation from comprehension studies;673
12.1.4.1.10;Behavioral evidence for embodiment in social cognition;673
12.1.4.2;Neural evidence for a modal nonmodular conceptual system;674
12.1.4.2.1;Category-specific deficits;674
12.1.4.2.2;Neuroimaging studies of category knowledge;674
12.1.4.3;Evidence for situated conceptualizations;676
12.1.4.3.1;Inferences about goal-relevant properties of the focal category;677
12.1.4.3.2;Evidence for setting inferences;677
12.1.4.3.3;Evidence for action inferences;678
12.1.4.3.4;Evidence for introspective state inferences;679
12.1.4.3.5;Evidence for dynamical simulations;680
12.1.5;Conclusion;681
12.1.5.1;Important issues for future research;682
12.1.5.1.1;Amodal symbols;682
12.1.5.1.2;Symbolic functions;683
12.1.5.1.3;Abstract concepts;683
12.1.6;Acknowledgment;684
12.1.7;References;684
12.2;Perceptual and Semantic Reorganization during Category Learning;688
12.2.1;Abstract;689
12.2.2;Introduction;690
12.2.3;Concept learning and perception;690
12.2.3.1;Object segmentation;691
12.2.3.2;Experiment 1;692
12.2.3.2.1;Method;693
12.2.3.2.2;Results and discussion;694
12.2.3.3;Experiment 2;694
12.2.3.3.1;Method;696
12.2.3.3.2;Results and discussion;697
12.2.3.4;Conclusions on perceptual reorganization;699
12.2.4;Semantic reorganization during category learning;701
12.2.4.1;Integral versus separable dimensions;701
12.2.4.2;Experiment 3;702
12.2.4.2.1;Method;703
12.2.4.2.2;Results and discussion;704
12.2.4.3;Experiment 4;706
12.2.4.3.1;Method;706
12.2.4.3.2;Results and discussion;706
12.2.5;Conclusions on semantic reorganization;708
12.2.6;Integrating perceptual and semantic reorganization;708
12.2.6.1;Characterizing psychological features;709
12.2.6.2;Characterizing featural change;710
12.2.6.3;Prospects for synthesizing perceptual and semantic reorganization;712
12.2.7;Acknowledgments;713
12.2.8;References;713
12.3;The Return of Concept Empiricism;716
12.3.1;Abstract;716
12.3.2;Introduction;717
12.3.3;Concept empiricism;717
12.3.3.1;Representing and doing: Two faces of concepts;717
12.3.3.2;Variable mechanisms;721
12.3.3.3;Perceptual vehicles;723
12.3.3.4;Innateness;725
12.3.3.5;Summary;728
12.3.4;The abstract ideas objections;729
12.3.5;References;731
13;Part 7 – Grounding, Recognition, and Reasoning in Categorization;734
13.1;Categorization, Reasoning, and Memory from a Neo-logical Point of View;736
13.1.1;Abstract;737
13.1.2;Introduction;738
13.1.3;Order, Information, and Categories;738
13.1.4;Inferences, Arguments, and Information;738
13.1.5;Logical and Creative Arguments;740
13.1.6;Types of Creative Arguments;740
13.1.7;Two Rather Incompatible Views in Cognitive Science;742
13.1.8;Experiments on Memory and Logical Competence;743
13.1.9;Logical Weakness and Classification of Errors;746
13.1.10;A New Theory of Logical Error and Logical Competence;747
13.1.11;The Cognitive Functions of Logic;748
13.1.12;Corrective Inferences and Cognitive Progress;750
13.1.13;The Fundamental Cognitive Function of Logical Reasoning;752
13.1.14;The Mind as a Dynamic System: Inference and Memory;752
13.1.15;General Conclusions: Categorization, Reasoning, and Memory;753
13.1.16;References;754
13.2;Approaches to Grounding Symbols in Perceptual and Sensorimotor Categories;756
13.2.1;Abstract;756
13.2.2;Cognitive symbol grounding;757
13.2.2.1;The symbol grounding problem;757
13.2.2.2;Grounding symbols in cognition;758
13.2.3;Linking vision and language: connectionist approaches to category learning and symbol grounding;761
13.2.3.1;Connectionist modeling of category learning and naming;761
13.2.3.2;Connectionist modeling of symbol grounding transfer;764
13.2.4;Linking vision, action and language: embodied approaches to language learning and evolution;766
13.2.4.1;Grounding symbols in simulated agents: The symbolic theft hypothesis;766
13.2.4.2;The emergence of language in robots;768
13.2.5;Discussion and conclusion;770
13.2.6;References;772
13.3;Embodied Categorization*;776
13.3.1;Abstract;777
13.3.2;Introduction: Embodied categorization;778
13.3.3;Purely reactive categorizers;780
13.3.3.1;The perceptual aliasing problem [Whitehead and Ballard (1991)];781
13.3.3.2;Type I versus II problems [Clark and Thornton (1997)];781
13.3.4;Reactive categorizers that learn;784
13.3.5;Representing categorizers;786
13.3.6;Emulating and simulating categorizers;789
13.3.6.1;Emulating categorizers;790
13.3.6.2;Simulating categorizers;792
13.3.6.2.1;Simulation of physical categories (folk physics);794
13.3.6.2.2;Simulation of functional categories (folk biology and mechanics);795
13.3.6.2.3;Simulation of intentional categories (folk psychology);795
13.3.7;Analogizing categorizers;796
13.3.8;Linguistic categorizers;798
13.3.9;Conclusion;798
13.3.10;References;799
13.4;Categorization of Objects, Scenes, and Faces through Time;804
13.4.1;Abstract;805
13.4.2;A model of categorization;806
13.4.3;Basic-level literature;809
13.4.4;Discrete processing cycles;810
13.4.4.1;A Bubbles primer;810
13.4.4.1.1;Stimulus Set?;810
13.4.4.1.2;Stimulus generation space?;811
13.4.4.1.3;The samples?;811
13.4.4.1.4;The task?;811
13.4.4.1.5;Response?;811
13.4.4.1.6;Observers?;812
13.4.4.2;Fossilized discrete processing cycles;812
13.4.4.3;What can temporal bubbles reveal about a SLIP categorizer?;814
13.4.5;The need for flexibility and a paradox;815
13.4.5.1;Limited processing capacity;815
13.4.5.2;The need for flexibility;816
13.4.5.3;Back to the paradox;817
13.4.6;Categorization as an iterative process;817
13.4.6.1;Compulsory feedforward processing sweeps;818
13.4.6.1.1;The nature of the information processed during compulsory feedforward sweeps;819
13.4.6.2;Flexible iterative processing sweeps;819
13.4.6.2.1;Empirical evidence for flexible and iterative processing sweeps;821
13.4.6.2.2;Deactivation studies;823
13.4.7;General discussion;823
13.4.8;References;825
13.5;Adaptive Categorization and Neural Networks*;830
13.5.1;Abstract;831
13.5.2;The problem of divergence;835
13.5.3;The solution: dual Hebbian/anti-Hebbian learning;836
13.5.3.1;Stabilization;837
13.5.3.2;Oscillation;838
13.5.3.3;Linearity;838
13.5.3.4;Additional properties of the learning rule;838
13.5.4;The Eidos model;839
13.5.5;The letter classification task;840
13.5.5.1;Methodology;840
13.5.5.2;Results;841
13.5.6;The problem of convergence;843
13.5.7;The solution: Unlearnin;845
13.5.8;The letter-classification task revisited;846
13.5.8.1;Methodology;846
13.5.8.2;Results;846
13.5.9;Current trends: Elimination of spurious attractors;849
13.5.10;Conclusion;850
13.5.11;References;851
13.6;A Grounded Mind in a Robotic Body;854
13.6.1;References;857
14;Part 8 – Machine Category Learning;858
14.1;Concept Learning and Nonmonotonic Reasoning¹;860
14.1.1;Abstract;861
14.1.2;The role of concepts;862
14.1.3;Three kinds of cognitive representations;862
14.1.4;Learning in symbolic systems;863
14.1.5;Learning in connectionist systems;864
14.1.6;Conceptual spaces as a representational framework;864
14.1.7;The origin of quality dimensions;866
14.1.8;Properties and concepts;868
14.1.9;Prototypes and conceptual spaces;869
14.1.10;Learning in conceptual spaces;871
14.1.11;The role of similarity in learning;873
14.1.12;Nonmonotonic aspects of concepts;875
14.1.12.1;Change from general category to subordinate;876
14.1.12.2;Context effects;877
14.1.13;Conclusion;878
14.1.14;References;879
14.2;Categorization in Symbolic Data Analysis;882
14.2.1;Abstract;883
14.2.2;Introduction;884
14.2.3;Categories, concepts, and symbolic data;885
14.2.3.1;From individuals to concepts;885
14.2.3.2;Categories in a database;886
14.2.3.3;From categories to concepts: reification of a category in a concept;886
14.2.3.4;Sources of symbolic data;888
14.2.4;Symbolic data tables and their background knowledge, concepts, and categories;889
14.2.4.1;Symbolic data tables;889
14.2.4.2;Building a symbolic data table by reification of categories in concepts;889
14.2.4.3;Description of concepts when the individuals are described by fuzzy data;890
14.2.4.4;Adding conceptual variables, joining concepts, and the DB2SO module of SODAS;891
14.2.5;Modeling concepts by “symbolic objects,” with certain philosophical aspects;892
14.2.5.1;Kinds of concepts and intuitive introduction of “symbolic objects”;892
14.2.5.2;Modeling concepts with four spaces: “individuals,” “concepts,” “descriptions,” and “symbolic objects”;892
14.2.5.3;Extent of concepts and symbolic objects;893
14.2.5.4;Syntax of symbolic objects in the case of “assertions”;895
14.2.5.5;Extent of a symbolic object;895
14.2.5.6;Concepts: Four approaches;895
14.2.6;Tools for symbolic objects;896
14.2.6.1;Order between symbolic objects;896
14.2.6.2;Finding a unique description for a concept: “T-norm of descriptive generalization”;896
14.2.6.3;Finding several descriptions for a concept;897
14.2.6.4;Dissimilarities between concepts;898
14.2.6.5;Finding prototypes from a concept;898
14.2.7;Underlying structures of symbolic objects;898
14.2.7.1;A generalized conceptual lattice;898
14.2.7.2;Mathematical framework of a symbolic data analysis;900
14.2.8;Steps and tools for Symbolic Data Analysis;900
14.2.8.1;Main steps;900
14.2.8.2;Descriptive SDA in SODAS;901
14.2.9;Overview of SODAS;902
14.2.9.1;Some advantages of the use of concepts modeled by symbolic objects;902
14.2.9.2;Overview of SODAS software;902
14.2.10;Final remarks;902
14.2.11;References;903
14.3;Category Formation in Self-organizing Embodied Agents;906
14.3.1;Abstract;906
14.3.2;Introduction;907
14.3.3;The method;907
14.3.4;Categories emerging from the interaction between the agent and the environment;908
14.3.4.1;Finding and remaining in favorable environmental areas;908
14.3.4.2;Discriminating objects with different shapes on the basis of tactile information;910
14.3.4.3;Behavior emerging from the dynamic interaction between the agent and its environment;913
14.3.5;Action-mediated sensory states;915
14.3.5.1;Discriminating larger and smaller cylindrical objects;916
14.3.5.2;Navigating toward a target area of the environment;918
14.3.6;Integrating sensorimotor information over time and the emergence of complex internal categories;920
14.3.6.1;The self-localization problem;921
14.3.7;Conclusions;924
14.3.8;Acknowledgments;925
14.3.9;References;925
14.4;An Information-based Discussion of Vagueness*: Six Scenarios Leading to Vagueness;928
14.4.1;Abstract;929
14.4.2;Introduction;930
14.4.3;The information framework;931
14.4.4;Classical vs. gradual properties;932
14.4.4.1;Graduality and partial preorderings;932
14.4.4.2;Membership functions as total preorders;933
14.4.4.3;Fuzzy sets and similarity to prototypes;934
14.4.4.4;Set-theoretic operations;934
14.4.4.5;Graduality is a useful form of vagueness;935
14.4.5;Precisely defined vs. poorly defined properties;936
14.4.5.1;Classification ambiguity;937
14.4.5.2;Vagueness as limited perception;937
14.4.5.3;Supervaluations;938
14.4.5.4;Ill-known partial membership;938
14.4.6;Refining precisely defined properties using closeness relations;938
14.4.7;Single agent vs. multiple agents;939
14.4.8;Ill-known attribute values and twofold sets;941
14.4.9;Approximately described sets;942
14.4.10;Concluding remarks;943
14.4.11;References;944
15;Part 9 – Data Mining for Categories and Ontologies;948
15.1;A Smooth Introduction to Symbolic Methods for Knowledge Discovery;950
15.1.1;Abstract;951
15.1.2;Introduction;952
15.1.3;Methods for KDD;953
15.1.3.1;An introductory example;953
15.1.3.2;Data mining methods;954
15.1.4;Lattice-based classification;955
15.1.5;Frequent itemset search and association rule extraction;957
15.1.5.1;Frequent itemset search;958
15.1.5.2;Association rule extraction;960
15.1.6;Applications;960
15.1.6.1;Mining chemical reaction database;961
15.1.6.1.1;The chemical context;961
15.1.6.1.2;Mining of a reaction database;962
15.1.6.1.3;Discussion;963
15.1.6.2;An experiment in biology;964
15.1.6.3;An introduction to Web mining;965
15.1.7;Discussion;967
15.1.8;Conclusion;967
15.1.9;References;968
15.2;Genre-Specific Text Mining and Extensional Inductive Concept Recognition: A Pseudocognitive Approach;972
15.2.1;Abstract;973
15.2.2;Introduction and definition of text mining (TM);974
15.2.2.1;Text mining;974
15.2.2.2;Our approach;975
15.2.3;Text retrieval;976
15.2.4;Standardization;977
15.2.5;Grammatical tagging;977
15.2.5.1;Why expert rules at the tagging stage?;978
15.2.5.1.1;The accuracy rates are correct, but this is still not “good enough”;978
15.2.5.1.2;Accuracy on what?;978
15.2.5.1.3;Recursion;978
15.2.5.2;A tagging language;979
15.2.5.3;Our approach to grammatical tagging;980
15.2.5.4;Automatic learning of new tagging rules;980
15.2.6;Terminology;981
15.2.7;Concept recognition in texts;981
15.2.7.1;Polysemy;982
15.2.7.2;General versus local collocations;982
15.2.7.3;Terms and collocations;982
15.2.7.4;ACT as a friendly interface helping the expert;983
15.2.7.5;ACT as an inductive program;984
15.2.7.6;Validation;988
15.2.7.6.1;Validation of the concepts;988
15.2.7.6.2;Validation of the induction;988
15.2.8;Conclusion;988
15.2.9;Acknowledgments;989
15.2.10;References;990
15.3;Classification and Categorization in Computer-Assisted Reading and Text Analysis;992
15.3.1;Abstract;993
15.3.2;Introduction;994
15.3.2.1;CARAT: General presentation;994
15.3.2.2;Difficulties with the technology;995
15.3.2.3;The nature of reading and analyzing a text;996
15.3.3;Definitions of classification and categorization for CARAT;998
15.3.4;Text classification and categorization;999
15.3.4.1;Text classification;999
15.3.4.2;Text categorization;999
15.3.4.3;Computer text classification and categorization;1000
15.3.5;Methodology for text classifying and categorizing;1000
15.3.5.1;Steps 1, 2, and 3: From a text to a matrix;1001
15.3.5.1.1;Step 1: Identification of units of information and domains of information;1001
15.3.5.1.2;Step 2: Cleaning and filtering;1002
15.3.5.1.3;Step 3: The matrix;1003
15.3.5.2;Steps 4 and 5;1004
15.3.5.2.1;The classification process;1004
15.3.5.2.2;The categorization process;1005
15.3.5.3;Step 6: Navigation;1005
15.3.5.4;Step 7: Evaluation;1005
15.3.6;Applications in CARAT;1006
15.3.6.1;Thematic analysis;1006
15.3.6.2;Categorical exploration of philosophical texts;1007
15.3.6.3;Content analysis;1009
15.3.7;The computer design: SATIM;1011
15.3.7.1;The workshop;1011
15.3.7.2;The laboratory;1012
15.3.7.3;Applications;1012
15.3.8;Conclusion;1013
15.3.9;References;1013
15.4;Graph Matching, System Design and Knowledge Modeling;1016
15.4.1;Abstract;1016
15.4.2;Introduction;1017
15.4.3;Knowledge represented as graph structures;1019
15.4.4;Learning heuristic knowledge;1021
15.4.5;Viability conditions;1022
15.4.6;The complexity of learning;1023
15.4.7;Categorization of knowledge in layers;1025
15.4.8;Conclusion;1026
15.4.9;References;1026
16;Part 10 – The Naturalization of Categories;1028
16.1;Nominalism and the Theory of Concepts;1030
16.1.1;Abstract;1030
16.1.2;Nominalism;1031
16.1.3;Ockham’s cleaver;1032
16.1.4;Motivations;1036
16.1.5;Nominalistic constraints for the theory of concepts;1038
16.1.5.1;Represented things as singular;1039
16.1.5.2;Representations as singular;1041
16.1.6;References;1043
16.2;Why do we think Racially?;1046
16.2.1;Abstract;1047
16.2.2;Introduction;1048
16.2.3;Is racialism a mere social construct?;1049
16.2.3.1;Racial skepticism;1049
16.2.3.2;Races are interactive kinds;1050
16.2.3.3;Races are transient kinds;1050
16.2.3.4;Merits and problems;1052
16.2.4;Is racialism a by-product of a human kind module?;1053
16.2.4.1;The nature of racialism;1053
16.2.4.2;The human kind module;1054
16.2.4.3;Empirical evidence;1054
16.2.4.4;Merits and problems;1056
16.2.5;Are races mere coalitions?;1058
16.2.5.1;Races and coalitions;1058
16.2.5.2;Empirical evidence;1058
16.2.5.3;Merits and problems;1059
16.2.6;Is racialism a by-product of an evolved ethnic cognitive system?;1061
16.2.6.1;“Ethnies” are not mere coalitions;1061
16.2.6.2;An adaptive scenario: Ethnic cognition and the exaptation of human folk biology;1062
16.2.6.3;Empirical evidence;1063
16.2.6.4;Merits and problems;1064
16.2.7;Conclusion;1066
16.2.8;References;1068
16.3;Neurosemantics and Categories;1072
16.3.1;Abstract;1073
16.3.2;Introduction;1074
16.3.2.1;Why “neuro”?;1074
16.3.2.2;The explanandum;1076
16.3.3;Mental representations as neural codes;1077
16.3.3.1;Representations;1077
16.3.3.2;Transformation;1078
16.3.3.3;A representational hierarchy;1079
16.3.4;The meaning of neural representations: Neurosemantics;1080
16.3.4.1;The representation relation;1080
16.3.4.2;A neurosemantic theory;1081
16.3.4.2.1;Systems;1081
16.3.4.2.2;Vehicles;1082
16.3.4.2.3;Referents;1083
16.3.4.2.4;Content;1084
16.3.4.3;Discussion;1086
16.3.5;Misrepresentation;1087
16.3.6;Conclusion;1089
16.3.7;References;1089
16.4;Conceptual Analysis and Philosophical Naturalism;1092
16.4.1;Abstract;1092
16.4.2;Introduction;1093
16.4.3;What is intuitive about conceptual analysis?;1094
16.4.4;Cognitive privileges, metaphysical privileges, and the Transparency Thesis;1095
16.4.5;Against privileges;1096
16.4.6;The inward approach;1098
16.4.7;Conceptual truths or truths about concepts?;1099
16.4.8;The outward approach;1101
16.4.9;‘Bachelors are unmarried men’ is about facts;1102
16.4.10;Explaining away the illusion;1104
16.4.11;A “mixed bag”;1105
16.4.12;Conclusion;1107
16.4.13;References;1107
16.5;Crisis! What Crisis?;1110
17;Index;1118