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Format: 1 Online-Ressource (XII, 294 Seiten) , Diagramme

ISBN: 9783030318468

Series Statement: Language, Cognition, and Mind 6

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-31844-4

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-31845-1

Language: English

Keywords: Sprache ; Semantik

DOI: 10.1007/978-3-030-31846-8

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

UID:

Format: 1 Online-Ressource (294 p.)

ISBN: 9783030318468

Series Statement: Language, Cognition, and Mind

Content: This open access book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science. The approach of this book is novel in more ways than one. Assuming the mental architecture and procedural modalities of Anderson’s ACT-R framework, it presents fine-grained computational models of human language processing tasks which make detailed quantitative predictions that can be checked against the results of self-paced reading and other psycho-linguistic experiments. All models are presented as computer programs that readers can run on their own computer and on inputs of their choice, thereby learning to design, program and run their own models. But even for readers who won't do all that, the book will show how such detailed, quantitatively predicting modeling of linguistic processes is possible. A methodological breakthrough and a must for anyone concerned about the future of linguistics! (Hans Kamp) This book constitutes a major step forward in linguistics and psycholinguistics. It constitutes a unique synthesis of several different research traditions: computational models of psycholinguistic processes, and formal models of semantics and discourse processing. The work also introduces a sophisticated python-based software environment for modeling linguistic processes. This book has the potential to revolutionize not only formal models of linguistics, but also models of language processing more generally. (Shravan Vasishth)

Note: English

Language: English

URL: kostenfrei

UID:

Format: 1 online resource (xii, 294 pages) : , illustrations (some color)

ISBN: 9783030318468 , 303031846X

Series Statement: Language, cognition, and mind, volume 6

Content: This open access book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science. The approach of this book is novel in more ways than one. Assuming the mental architecture and procedural modalities of Anderson's ACT-R framework, it presents fine-grained computational models of human language processing tasks which make detailed quantitative predictions that can be checked against the results of self-paced reading and other psycho-linguistic experiments. All models are presented as computer programs that readers can run on their own computer and on inputs of their choice, thereby learning to design, program and run their own models. But even for readers who won't do all that, the book will show how such detailed, quantitatively predicting modeling of linguistic processes is possible. A methodological breakthrough and a must for anyone concerned about the future of linguistics! (Hans Kamp) This book constitutes a major step forward in linguistics and psycholinguistics. It constitutes a unique synthesis of several different research traditions: computational models of psycholinguistic processes, and formal models of semantics and discourse processing. The work also introduces a sophisticated python-based software environment for modeling linguistic processes. This book has the potential to revolutionize not only formal models of linguistics, but also models of language processing more generally. (Shravan Vasishth).

Note: Chapter 1. Introduction -- Chapter 2. The ACT-R cognitive architecture and its pyactr implementation -- Chapter 3. The basics of syntactic parsing in ACT-R -- Chapter 4. Syntax as a Cognitive Process: Left-corner parsing with visual & motor interfaces -- Chapter 5. Brief introduction to Bayesian methods and pymc3 for linguists -- Chapter 6. Modeling linguistic performance -- Chapter 7. Competence-performance models for lexical access and syntactic parsing -- Chapter 8. Semantics as a cognitive process I: Discourse Representation Structures in declarative memory -- Chapter 9. Semantics as a cognitive process II: Active search for cataphora antecedents and the semantics of conditionals -- Chapter 10. Future directions.

Language: English

DOI: 10.1007/978-3-030-31846-8

URL: ProQuest Ebook Central

URL: SpringerLink

UID:

Format: XII, 294 p. 267 illus., 25 illus. in color. , online resource.

Edition: 1st ed. 2020.

ISBN: 9783030318468

Series Statement: Language, Cognition, and Mind, 6

Content: This open access book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science. The approach of this book is novel in more ways than one. Assuming the mental architecture and procedural modalities of Anderson's ACT-R framework, it presents fine-grained computational models of human language processing tasks which make detailed quantitative predictions that can be checked against the results of self-paced reading and other psycho-linguistic experiments. All models are presented as computer programs that readers can run on their own computer and on inputs of their choice, thereby learning to design, program and run their own models. But even for readers who won't do all that, the book will show how such detailed, quantitatively predicting modeling of linguistic processes is possible. A methodological breakthrough and a must for anyone concerned about the future of linguistics! (Hans Kamp) This book constitutes a major step forward in linguistics and psycholinguistics. It constitutes a unique synthesis of several different research traditions: computational models of psycholinguistic processes, and formal models of semantics and discourse processing. The work also introduces a sophisticated python-based software environment for modeling linguistic processes. This book has the potential to revolutionize not only formal models of linguistics, but also models of language processing more generally. (Shravan Vasishth) .

Note: Chapter 1. Introduction -- Chapter 2. The ACT-R cognitive architecture and its pyactr implementation -- Chapter 3. The basics of syntactic parsing in ACT-R -- Chapter 4. Syntax as a Cognitive Process: Left-corner parsing with visual & motor interfaces -- Chapter 5. Brief introduction to Bayesian methods and pymc3 for linguists -- Chapter 6. Modeling linguistic performance -- Chapter 7. Competence-performance models for lexical access and syntactic parsing -- Chapter 8. Semantics as a cognitive process I: Discourse Representation Structures in declarative memory -- Chapter 9. Semantics as a cognitive process II: Active search for cataphora antecedents and the semantics of conditionals -- Chapter 10. Future directions.

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783030318444

Additional Edition: Printed edition: ISBN 9783030318451

Language: English

DOI: 10.1007/978-3-030-31846-8

URL: https://doi.org/10.1007/978-3-030-31846-8

UID:

Format: 1 online resource (299 pages)

Edition: 1st ed.

ISBN: 9783030318468

Series Statement: Language, Cognition, and Mind Series ; v.6

Note: Intro -- Foreword and Acknowledgments -- Contents -- 1 Introduction -- 1.1 Background Knowledge -- 1.2 The Structure of the Book -- 2 The ACT-R Cognitive Architecture and Its pyactr Implementation -- 2.1 Cognitive Architectures and ACT-R -- 2.2 ACT-R in Cognitive Science and Linguistics -- 2.3 ACT-R Implementation -- 2.4 Knowledge in ACT-R -- 2.4.1 Declarative Memory: Chunks -- 2.4.2 Procedural Memory: Productions -- 2.5 The Basics of pyactr: Declaring Chunks -- 2.6 Modules and Buffers -- 2.7 Writing Productions in pyactr -- 2.8 Running Our First Model -- 2.9 Some More Models -- 2.9.1 The Counting Model -- 2.9.2 Regular Grammars in ACT-R -- 2.9.3 Counter Automata in ACT-R -- 2.10 Appendix: The Four Models for Agreement, Counting, Regular Grammars and Counter Automata -- 3 The Basics of Syntactic Parsing in ACT-R -- 3.1 Top-Down Parsing -- 3.2 Building a Top-Down Parser in pyactr -- 3.2.1 Modules, Buffers, and the Lexicon -- 3.2.2 Production Rules -- 3.3 Running the Model -- 3.4 Failures to Parse and Taking Snapshots of the Mind When It Fails -- 3.5 Top-Down Parsing as an Imperfect Psycholinguistic Model -- 3.6 Appendix: The Top-Down Parser -- 4 Syntax as a Cognitive Process: Left-Corner Parsing with Visual and Motor Interfaces -- 4.1 The Environment in ACT-R: Modeling Lexical Decision Tasks -- 4.1.1 The Visual Module -- 4.1.2 The Motor Module -- 4.2 The Lexical Decision Model: Productions -- 4.3 Running the Lexical Decision Model and Understanding the Output -- 4.3.1 Visual Processes in Our Lexical Decision Model -- 4.3.2 Manual Processes in Our Lexical Decision Model -- 4.4 A Left-Corner Parser with Visual and Motor Interfaces -- 4.5 Appendix: The Lexical Decision Model -- 5 Brief Introduction to Bayesian Methods and pymc3 for Linguists -- 5.1 The Python Libraries We Need -- 5.2 The Data. , 5.3 Prior Beliefs and the Basics of pymc3, matplotlib and seaborn -- 5.4 Our Function for Generating the Data (The Likelihood) -- 5.5 Posterior Beliefs: Estimating the Model Parameters and Answering the Theoretical Question -- 5.6 Conclusion -- 5.7 Appendix -- 6 Modeling Linguistic Performance -- 6.1 The Power Law of Forgetting -- 6.2 The Base Activation Equation -- 6.3 The Attentional Weighting Equation -- 6.4 Activation, Retrieval Probability and Retrieval Latency -- 6.5 Appendix -- 7 Competence-Performance Models for Lexical Access and Syntactic Parsing -- 7.1 The Log-Frequency Model of Lexical Decision -- 7.2 The Simplest ACT-R Model of Lexical Decision -- 7.3 The Second ACT-R Model of Lexical Decision: Adding the Latency Exponent -- 7.4 Bayes+ACT-R: Quantitative Comparison for Qualitative Theories -- 7.4.1 The Bayes+ACT-R Lexical Decision Model Without the Imaginal Buffer -- 7.4.2 Bayes+ACT-R Lexical Decision with Imaginal-Buffer Involvement and Default Encoding Delay for the Imaginal Buffer -- 7.4.3 Bayes+ACT-R Lexical Decision with Imaginal Buffer and 0 Delay -- 7.5 Modeling Self-paced Reading with a Left-Corner Parser -- 7.6 Conclusion -- 7.7 Appendix: The Bayes and Bayes+ACT-R Models -- 7.7.1 Lexical Decision Models -- 7.7.2 Left-Corner Parser Models -- 8 Semantics as a Cognitive Process I: Discourse Representation Structures in Declarative Memory -- 8.1 The Fan Effect and the Retrieval of DRSs from Declarative Memory -- 8.2 The Fan Effect Reflects the Way Meaning Representations (DRSs) Are Organized in Declarative Memory -- 8.3 Integrating ACT-R and DRT: An Eager Left-Corner Syntax/Semantics Parser -- 8.4 Semantic (Truth-Value) Evaluation as Memory Retrieval, and Fitting the Model to Data -- 8.5 Model Discussion and Summary -- 8.6 Appendix: End-to-End Model of the Fan Effect with an Explicit Syntax/Semantics Parser. , 8.6.1 File ch8/parser_dm_fan.py -- 8.6.2 File ch8/parser_rules_fan.py -- 8.6.3 File ch8/run_parser_fan.py -- 8.6.4 File ch8/estimate_parser_fan.py -- 9 Semantics as a Cognitive Process II: Active Search for Cataphora Antecedents and the Semantics of Conditionals -- 9.1 Two Experiments Studying the Interaction Between Conditionals and Cataphora -- 9.1.1 Experiment 1: Anaphora Versus Cataphora in Conjunctions Versus Conditionals -- 9.1.2 Experiment 2: Cataphoric Presuppositions in Conjunctions Versus Conditionals -- 9.2 Mechanistic Processing Models as an Explanatory Goal for Semantics -- 9.3 Modeling the Interaction of Conditionals and Pronominal Cataphora -- 9.3.1 Chunk Types and the Lexical Information Stored in Declarative Memory -- 9.3.2 Rules to Advance Dref Peg Positions, Key Presses and Word-Related Rules -- 9.3.3 Phrase Structure Rules -- 9.3.4 Rules for Conjunctions and Anaphora Resolution -- 9.3.5 Rules for Conditionals and Cataphora Resolution -- 9.4 Modeling the Interaction of Conditionals and Cataphoric Presuppositions -- 9.4.1 Rules for `Again' and Presupposition Resolution -- 9.4.2 Rules for `Maximize Presupposition' -- 9.4.3 Fitting the Model to the Experiment 2 Data -- 9.5 Conclusion -- 9.6 Appendix: The Complete Syntax/Semantics Parser -- 9.6.1 File ch9/parser_dm.py -- 9.6.2 File ch9/parser_rules.py -- 9.6.3 File ch9/run_parser.py -- 9.6.4 File ch9/estimate_parser_parallel.py -- 10 Future Directions -- Appendix Bibliography.

Additional Edition: Print version: Brasoveanu, Adrian Computational Cognitive Modeling and Linguistic Theory Cham : Springer International Publishing AG,c2020 ISBN 9783030318444

Language: English

Keywords: Electronic books.

URL: Click to View

UID:

Format: 1 online resource (XII, 294 p. 267 illus., 25 illus. in color.)

Edition: 1st ed. 2020.

ISBN: 3-030-31846-X

Series Statement: Language, Cognition, and Mind, 6

Content: This open access book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science. The approach of this book is novel in more ways than one. Assuming the mental architecture and procedural modalities of Anderson’s ACT-R framework, it presents fine-grained computational models of human language processing tasks which make detailed quantitative predictions that can be checked against the results of self-paced reading and other psycho-linguistic experiments. All models are presented as computer programs that readers can run on their own computer and on inputs of their choice, thereby learning to design, program and run their own models. But even for readers who won't do all that, the book will show how such detailed, quantitatively predicting modeling of linguistic processes is possible. A methodological breakthrough and a must for anyone concerned about the future of linguistics! (Hans Kamp) This book constitutes a major step forward in linguistics and psycholinguistics. It constitutes a unique synthesis of several different research traditions: computational models of psycholinguistic processes, and formal models of semantics and discourse processing. The work also introduces a sophisticated python-based software environment for modeling linguistic processes. This book has the potential to revolutionize not only formal models of linguistics, but also models of language processing more generally. (Shravan Vasishth) .

Note: Chapter 1. Introduction -- Chapter 2. The ACT-R cognitive architecture and its pyactr implementation -- Chapter 3. The basics of syntactic parsing in ACT-R -- Chapter 4. Syntax as a Cognitive Process: Left-corner parsing with visual & motor interfaces -- Chapter 5. Brief introduction to Bayesian methods and pymc3 for linguists -- Chapter 6. Modeling linguistic performance -- Chapter 7. Competence-performance models for lexical access and syntactic parsing -- Chapter 8. Semantics as a cognitive process I: Discourse Representation Structures in declarative memory -- Chapter 9. Semantics as a cognitive process II: Active search for cataphora antecedents and the semantics of conditionals -- Chapter 10. Future directions. , English

Additional Edition: ISBN 3-030-31844-3

Language: English

DOI: 10.1007/978-3-030-31846-8

UID:

Format: 1 online resource (XII, 294 p. 267 illus., 25 illus. in color.)

Edition: 1st ed. 2020.

ISBN: 3-030-31846-X

Series Statement: Language, Cognition, and Mind, 6

Content: This open access book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science. The approach of this book is novel in more ways than one. Assuming the mental architecture and procedural modalities of Anderson’s ACT-R framework, it presents fine-grained computational models of human language processing tasks which make detailed quantitative predictions that can be checked against the results of self-paced reading and other psycho-linguistic experiments. All models are presented as computer programs that readers can run on their own computer and on inputs of their choice, thereby learning to design, program and run their own models. But even for readers who won't do all that, the book will show how such detailed, quantitatively predicting modeling of linguistic processes is possible. A methodological breakthrough and a must for anyone concerned about the future of linguistics! (Hans Kamp) This book constitutes a major step forward in linguistics and psycholinguistics. It constitutes a unique synthesis of several different research traditions: computational models of psycholinguistic processes, and formal models of semantics and discourse processing. The work also introduces a sophisticated python-based software environment for modeling linguistic processes. This book has the potential to revolutionize not only formal models of linguistics, but also models of language processing more generally. (Shravan Vasishth) .

Note: Chapter 1. Introduction -- Chapter 2. The ACT-R cognitive architecture and its pyactr implementation -- Chapter 3. The basics of syntactic parsing in ACT-R -- Chapter 4. Syntax as a Cognitive Process: Left-corner parsing with visual & motor interfaces -- Chapter 5. Brief introduction to Bayesian methods and pymc3 for linguists -- Chapter 6. Modeling linguistic performance -- Chapter 7. Competence-performance models for lexical access and syntactic parsing -- Chapter 8. Semantics as a cognitive process I: Discourse Representation Structures in declarative memory -- Chapter 9. Semantics as a cognitive process II: Active search for cataphora antecedents and the semantics of conditionals -- Chapter 10. Future directions. , English

Additional Edition: ISBN 3-030-31844-3

Language: English

DOI: 10.1007/978-3-030-31846-8

UID:

Format: 1 online resource (XII, 294 p. 267 illus., 25 illus. in color.)

Edition: 1st ed. 2020.

ISBN: 3-030-31846-X

Series Statement: Language, Cognition, and Mind, 6

Content: This open access book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science. The approach of this book is novel in more ways than one. Assuming the mental architecture and procedural modalities of Anderson’s ACT-R framework, it presents fine-grained computational models of human language processing tasks which make detailed quantitative predictions that can be checked against the results of self-paced reading and other psycho-linguistic experiments. All models are presented as computer programs that readers can run on their own computer and on inputs of their choice, thereby learning to design, program and run their own models. But even for readers who won't do all that, the book will show how such detailed, quantitatively predicting modeling of linguistic processes is possible. A methodological breakthrough and a must for anyone concerned about the future of linguistics! (Hans Kamp) This book constitutes a major step forward in linguistics and psycholinguistics. It constitutes a unique synthesis of several different research traditions: computational models of psycholinguistic processes, and formal models of semantics and discourse processing. The work also introduces a sophisticated python-based software environment for modeling linguistic processes. This book has the potential to revolutionize not only formal models of linguistics, but also models of language processing more generally. (Shravan Vasishth) .

Note: Chapter 1. Introduction -- Chapter 2. The ACT-R cognitive architecture and its pyactr implementation -- Chapter 3. The basics of syntactic parsing in ACT-R -- Chapter 4. Syntax as a Cognitive Process: Left-corner parsing with visual & motor interfaces -- Chapter 5. Brief introduction to Bayesian methods and pymc3 for linguists -- Chapter 6. Modeling linguistic performance -- Chapter 7. Competence-performance models for lexical access and syntactic parsing -- Chapter 8. Semantics as a cognitive process I: Discourse Representation Structures in declarative memory -- Chapter 9. Semantics as a cognitive process II: Active search for cataphora antecedents and the semantics of conditionals -- Chapter 10. Future directions. , English

Additional Edition: ISBN 3-030-31844-3

Language: English

DOI: 10.1007/978-3-030-31846-8

UID:

Format: 1 Online-Ressource (XII, 294 Seiten) : , Diagramme.

ISBN: 978-3-030-31846-8

Series Statement: Language, Cognition, and Mind 6

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-31844-4

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-31845-1

Language: English

Keywords: Sprache ; Semantik

DOI: 10.1007/978-3-030-31846-8

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

UID:

Format: 1 Online-Ressource (XII, 294 Seiten) : , Diagramme.

ISBN: 978-3-030-31846-8

Series Statement: Language, Cognition, and Mind 6

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-31844-4

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-31845-1

Language: English

Keywords: Sprache ; Semantik

DOI: 10.1007/978-3-030-31846-8

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)