Descriptive and normative approaches to human behavior /:
The aim of the book is to present side-by-side representative and cutting-edge samples of work in mathematical psychology and the analytic philosophy with prominent use of mathematical formalisms.
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New Jersey :
World Scientific,
©2012.
|
| Schriftenreihe: | Advanced series on mathematical psychology ;
v. 3. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | The aim of the book is to present side-by-side representative and cutting-edge samples of work in mathematical psychology and the analytic philosophy with prominent use of mathematical formalisms. |
| Beschreibung: | 1 online resource (viii, 324 pages) : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9814368016 9789814368018 |
Internformat
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| 490 | 1 | |a Advanced series on mathematical psychology ; |v v. 3 | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Preface; Contents; 1. The Impossibility of a Satisfactory Population Ethics Gustaf Arrhenius; 1.1. Introduction; 1.2. The Basic Structure; 1.3. Adequacy Conditions; 1.4. The Impossibility Theorem; 1.4.1. Lemma 1.1; 1.4.2. Lemma 1.2; 1.4.3. Lemma 1.3; 1.4.4. Lemma 1.4; 1.5. Discussion; Acknowledgments; References; 2. Explaining Interference Effects Using Quantum Probability Theory Jerome R. Busemeyer and Jennifer S. Trueblood; 2.1. Introduction; 2.2. What Is an Interference Effect?; 2.3. What Is the Evidence for Interference Effects?; 2.3.1. Perception of ambiguous figures. | |
| 505 | 8 | |a 2.3.2. Categorization -- decision making2.3.3. Disjunction effect in decision making; 2.4. What Are the Explanations for These Effects?; 2.4.1. Markov model; 2.4.2. Quantum model; 2.4.3. Quantum noise model; 2.5. What Next?; References; 3. Defining Goodness and Badness in Terms of Betterness Without Negation Erik Carlson; 3.1. Introduction; 3.2. Assumptions; 3.3. Defining the Monadic Value Predicates; 3.4. Incomparability and Indeterminacy; 3.5. Giving Up Monotonicity; 3.6. Conclusion; Acknowledgments; Appendix: Proofs.; References. | |
| 505 | 8 | |a 4. Optimality in Multisensory Integration Dynamics: Normative and Descriptive Aspects Hans Colonius and Adele Diederich4.1. Introduction; 4.1.1. Two basic experimental paradigms; 4.1.2. The race model; 4.2. Time Window of Integration (TWIN) Model: Assumptions and Predictions; 4.2.1. Deriving TWIN predictions for RTP and FAP; 4.3. Towards an Optimal Time Window of Integration; 4.3.1. The basic decision situation; 4.3.2. Deriving an optimal decision rule; 4.3.3. Optimal time window in focused attention paradigm; 4.4. Two Empirical Studies of Time Window Optimality. | |
| 505 | 8 | |a 4.4.1. The effect of prior probability: The van Wanrooij et al. 2010 study4.4.2. The effect of age: The Diederich et al. 2008 study; 4.5. Summary and Outlook; Acknowledgments; Appendix 1; Appendix 2; References; 5. On the Reverse Problem of Fechnerian Scaling Ehtibar N. Dzhafarov; 5.1. Background; 5.2. Problem; 5.3. General Considerations; 5.4. Special Stimulus Spaces; 5.4.1. Directly linked spaces; 5.4.2. Spaces with metric-in-the-small dissimilarities; 5.4.3. Uniformly discrete spaces; Acknowledgments; References; 6. Bayesian Adaptive Estimation: A Theoretical Review Janne V. Kujala. | |
| 505 | 8 | |a 6.1. Introduction6.1.1. Psychophysics; 6.1.2. The greedy strategy; 6.1.3. The entropy loss function and mutual information; 6.1.4. Calculating expected information gain; 6.1.5. Nuisance variables and utility weights; 6.1.6. Global strategies; 6.1. 7. The globally optimal strategy; 6.1.8. Non-adaptive and batch strategies; 6.2. Examples; 6.2.1. A simplified psychometric model; 6.2.1.1. Success of the greedy strategy; 6.2.1.2. Non-adaptive and batch strategies; 6.2.1.3. Comparison; 6.2.2. Exploration versus exploitation; 6.2.3. Inappropriate utility function; 6.3. Random Cost of Observation. | |
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| contents | Preface; Contents; 1. The Impossibility of a Satisfactory Population Ethics Gustaf Arrhenius; 1.1. Introduction; 1.2. The Basic Structure; 1.3. Adequacy Conditions; 1.4. The Impossibility Theorem; 1.4.1. Lemma 1.1; 1.4.2. Lemma 1.2; 1.4.3. Lemma 1.3; 1.4.4. Lemma 1.4; 1.5. Discussion; Acknowledgments; References; 2. Explaining Interference Effects Using Quantum Probability Theory Jerome R. Busemeyer and Jennifer S. Trueblood; 2.1. Introduction; 2.2. What Is an Interference Effect?; 2.3. What Is the Evidence for Interference Effects?; 2.3.1. Perception of ambiguous figures. 2.3.2. Categorization -- decision making2.3.3. Disjunction effect in decision making; 2.4. What Are the Explanations for These Effects?; 2.4.1. Markov model; 2.4.2. Quantum model; 2.4.3. Quantum noise model; 2.5. What Next?; References; 3. Defining Goodness and Badness in Terms of Betterness Without Negation Erik Carlson; 3.1. Introduction; 3.2. Assumptions; 3.3. Defining the Monadic Value Predicates; 3.4. Incomparability and Indeterminacy; 3.5. Giving Up Monotonicity; 3.6. Conclusion; Acknowledgments; Appendix: Proofs.; References. 4. Optimality in Multisensory Integration Dynamics: Normative and Descriptive Aspects Hans Colonius and Adele Diederich4.1. Introduction; 4.1.1. Two basic experimental paradigms; 4.1.2. The race model; 4.2. Time Window of Integration (TWIN) Model: Assumptions and Predictions; 4.2.1. Deriving TWIN predictions for RTP and FAP; 4.3. Towards an Optimal Time Window of Integration; 4.3.1. The basic decision situation; 4.3.2. Deriving an optimal decision rule; 4.3.3. Optimal time window in focused attention paradigm; 4.4. Two Empirical Studies of Time Window Optimality. 4.4.1. The effect of prior probability: The van Wanrooij et al. 2010 study4.4.2. The effect of age: The Diederich et al. 2008 study; 4.5. Summary and Outlook; Acknowledgments; Appendix 1; Appendix 2; References; 5. On the Reverse Problem of Fechnerian Scaling Ehtibar N. Dzhafarov; 5.1. Background; 5.2. Problem; 5.3. General Considerations; 5.4. Special Stimulus Spaces; 5.4.1. Directly linked spaces; 5.4.2. Spaces with metric-in-the-small dissimilarities; 5.4.3. Uniformly discrete spaces; Acknowledgments; References; 6. Bayesian Adaptive Estimation: A Theoretical Review Janne V. Kujala. 6.1. Introduction6.1.1. Psychophysics; 6.1.2. The greedy strategy; 6.1.3. The entropy loss function and mutual information; 6.1.4. Calculating expected information gain; 6.1.5. Nuisance variables and utility weights; 6.1.6. Global strategies; 6.1. 7. The globally optimal strategy; 6.1.8. Non-adaptive and batch strategies; 6.2. Examples; 6.2.1. A simplified psychometric model; 6.2.1.1. Success of the greedy strategy; 6.2.1.2. Non-adaptive and batch strategies; 6.2.1.3. Comparison; 6.2.2. Exploration versus exploitation; 6.2.3. Inappropriate utility function; 6.3. Random Cost of Observation. |
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| dewey-ones | 155 - Differential & developmental psychology |
| dewey-raw | 155.2 |
| dewey-search | 155.2 |
| dewey-sort | 3155.2 |
| dewey-tens | 150 - Psychology |
| discipline | Psychologie |
| format | Electronic eBook |
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| indexdate | 2024-11-27T13:18:12Z |
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| series | Advanced series on mathematical psychology ; |
| series2 | Advanced series on mathematical psychology ; |
| spelling | Descriptive and normative approaches to human behavior / editors Ehtibar Dzhafarov, Lacey Perry. New Jersey : World Scientific, ©2012. 1 online resource (viii, 324 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Advanced series on mathematical psychology ; v. 3 Includes bibliographical references and index. Preface; Contents; 1. The Impossibility of a Satisfactory Population Ethics Gustaf Arrhenius; 1.1. Introduction; 1.2. The Basic Structure; 1.3. Adequacy Conditions; 1.4. The Impossibility Theorem; 1.4.1. Lemma 1.1; 1.4.2. Lemma 1.2; 1.4.3. Lemma 1.3; 1.4.4. Lemma 1.4; 1.5. Discussion; Acknowledgments; References; 2. Explaining Interference Effects Using Quantum Probability Theory Jerome R. Busemeyer and Jennifer S. Trueblood; 2.1. Introduction; 2.2. What Is an Interference Effect?; 2.3. What Is the Evidence for Interference Effects?; 2.3.1. Perception of ambiguous figures. 2.3.2. Categorization -- decision making2.3.3. Disjunction effect in decision making; 2.4. What Are the Explanations for These Effects?; 2.4.1. Markov model; 2.4.2. Quantum model; 2.4.3. Quantum noise model; 2.5. What Next?; References; 3. Defining Goodness and Badness in Terms of Betterness Without Negation Erik Carlson; 3.1. Introduction; 3.2. Assumptions; 3.3. Defining the Monadic Value Predicates; 3.4. Incomparability and Indeterminacy; 3.5. Giving Up Monotonicity; 3.6. Conclusion; Acknowledgments; Appendix: Proofs.; References. 4. Optimality in Multisensory Integration Dynamics: Normative and Descriptive Aspects Hans Colonius and Adele Diederich4.1. Introduction; 4.1.1. Two basic experimental paradigms; 4.1.2. The race model; 4.2. Time Window of Integration (TWIN) Model: Assumptions and Predictions; 4.2.1. Deriving TWIN predictions for RTP and FAP; 4.3. Towards an Optimal Time Window of Integration; 4.3.1. The basic decision situation; 4.3.2. Deriving an optimal decision rule; 4.3.3. Optimal time window in focused attention paradigm; 4.4. Two Empirical Studies of Time Window Optimality. 4.4.1. The effect of prior probability: The van Wanrooij et al. 2010 study4.4.2. The effect of age: The Diederich et al. 2008 study; 4.5. Summary and Outlook; Acknowledgments; Appendix 1; Appendix 2; References; 5. On the Reverse Problem of Fechnerian Scaling Ehtibar N. Dzhafarov; 5.1. Background; 5.2. Problem; 5.3. General Considerations; 5.4. Special Stimulus Spaces; 5.4.1. Directly linked spaces; 5.4.2. Spaces with metric-in-the-small dissimilarities; 5.4.3. Uniformly discrete spaces; Acknowledgments; References; 6. Bayesian Adaptive Estimation: A Theoretical Review Janne V. Kujala. 6.1. Introduction6.1.1. Psychophysics; 6.1.2. The greedy strategy; 6.1.3. The entropy loss function and mutual information; 6.1.4. Calculating expected information gain; 6.1.5. Nuisance variables and utility weights; 6.1.6. Global strategies; 6.1. 7. The globally optimal strategy; 6.1.8. Non-adaptive and batch strategies; 6.2. Examples; 6.2.1. A simplified psychometric model; 6.2.1.1. Success of the greedy strategy; 6.2.1.2. Non-adaptive and batch strategies; 6.2.1.3. Comparison; 6.2.2. Exploration versus exploitation; 6.2.3. Inappropriate utility function; 6.3. Random Cost of Observation. The aim of the book is to present side-by-side representative and cutting-edge samples of work in mathematical psychology and the analytic philosophy with prominent use of mathematical formalisms. Psychology Mathematical models. http://id.loc.gov/authorities/subjects/sh85108463 Analysis (Philosophy) Mathematical models. Psychologie Modèles mathématiques. Philosophie analytique Modèles mathématiques. PSYCHOLOGY Personality. bisacsh Psychology Mathematical models fast Dzhafarov, Ehtibar N. Perry, Lacey. Print version: 9789814368001 9814368008 (DLC) 2011027639 Advanced series on mathematical psychology ; v. 3. http://id.loc.gov/authorities/names/n2004008449 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=426441 Volltext |
| spellingShingle | Descriptive and normative approaches to human behavior / Advanced series on mathematical psychology ; Preface; Contents; 1. The Impossibility of a Satisfactory Population Ethics Gustaf Arrhenius; 1.1. Introduction; 1.2. The Basic Structure; 1.3. Adequacy Conditions; 1.4. The Impossibility Theorem; 1.4.1. Lemma 1.1; 1.4.2. Lemma 1.2; 1.4.3. Lemma 1.3; 1.4.4. Lemma 1.4; 1.5. Discussion; Acknowledgments; References; 2. Explaining Interference Effects Using Quantum Probability Theory Jerome R. Busemeyer and Jennifer S. Trueblood; 2.1. Introduction; 2.2. What Is an Interference Effect?; 2.3. What Is the Evidence for Interference Effects?; 2.3.1. Perception of ambiguous figures. 2.3.2. Categorization -- decision making2.3.3. Disjunction effect in decision making; 2.4. What Are the Explanations for These Effects?; 2.4.1. Markov model; 2.4.2. Quantum model; 2.4.3. Quantum noise model; 2.5. What Next?; References; 3. Defining Goodness and Badness in Terms of Betterness Without Negation Erik Carlson; 3.1. Introduction; 3.2. Assumptions; 3.3. Defining the Monadic Value Predicates; 3.4. Incomparability and Indeterminacy; 3.5. Giving Up Monotonicity; 3.6. Conclusion; Acknowledgments; Appendix: Proofs.; References. 4. Optimality in Multisensory Integration Dynamics: Normative and Descriptive Aspects Hans Colonius and Adele Diederich4.1. Introduction; 4.1.1. Two basic experimental paradigms; 4.1.2. The race model; 4.2. Time Window of Integration (TWIN) Model: Assumptions and Predictions; 4.2.1. Deriving TWIN predictions for RTP and FAP; 4.3. Towards an Optimal Time Window of Integration; 4.3.1. The basic decision situation; 4.3.2. Deriving an optimal decision rule; 4.3.3. Optimal time window in focused attention paradigm; 4.4. Two Empirical Studies of Time Window Optimality. 4.4.1. The effect of prior probability: The van Wanrooij et al. 2010 study4.4.2. The effect of age: The Diederich et al. 2008 study; 4.5. Summary and Outlook; Acknowledgments; Appendix 1; Appendix 2; References; 5. On the Reverse Problem of Fechnerian Scaling Ehtibar N. Dzhafarov; 5.1. Background; 5.2. Problem; 5.3. General Considerations; 5.4. Special Stimulus Spaces; 5.4.1. Directly linked spaces; 5.4.2. Spaces with metric-in-the-small dissimilarities; 5.4.3. Uniformly discrete spaces; Acknowledgments; References; 6. Bayesian Adaptive Estimation: A Theoretical Review Janne V. Kujala. 6.1. Introduction6.1.1. Psychophysics; 6.1.2. The greedy strategy; 6.1.3. The entropy loss function and mutual information; 6.1.4. Calculating expected information gain; 6.1.5. Nuisance variables and utility weights; 6.1.6. Global strategies; 6.1. 7. The globally optimal strategy; 6.1.8. Non-adaptive and batch strategies; 6.2. Examples; 6.2.1. A simplified psychometric model; 6.2.1.1. Success of the greedy strategy; 6.2.1.2. Non-adaptive and batch strategies; 6.2.1.3. Comparison; 6.2.2. Exploration versus exploitation; 6.2.3. Inappropriate utility function; 6.3. Random Cost of Observation. Psychology Mathematical models. http://id.loc.gov/authorities/subjects/sh85108463 Analysis (Philosophy) Mathematical models. Psychologie Modèles mathématiques. Philosophie analytique Modèles mathématiques. PSYCHOLOGY Personality. bisacsh Psychology Mathematical models fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85108463 |
| title | Descriptive and normative approaches to human behavior / |
| title_auth | Descriptive and normative approaches to human behavior / |
| title_exact_search | Descriptive and normative approaches to human behavior / |
| title_full | Descriptive and normative approaches to human behavior / editors Ehtibar Dzhafarov, Lacey Perry. |
| title_fullStr | Descriptive and normative approaches to human behavior / editors Ehtibar Dzhafarov, Lacey Perry. |
| title_full_unstemmed | Descriptive and normative approaches to human behavior / editors Ehtibar Dzhafarov, Lacey Perry. |
| title_short | Descriptive and normative approaches to human behavior / |
| title_sort | descriptive and normative approaches to human behavior |
| topic | Psychology Mathematical models. http://id.loc.gov/authorities/subjects/sh85108463 Analysis (Philosophy) Mathematical models. Psychologie Modèles mathématiques. Philosophie analytique Modèles mathématiques. PSYCHOLOGY Personality. bisacsh Psychology Mathematical models fast |
| topic_facet | Psychology Mathematical models. Analysis (Philosophy) Mathematical models. Psychologie Modèles mathématiques. Philosophie analytique Modèles mathématiques. PSYCHOLOGY Personality. Psychology Mathematical models |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=426441 |
| work_keys_str_mv | AT dzhafarovehtibarn descriptiveandnormativeapproachestohumanbehavior AT perrylacey descriptiveandnormativeapproachestohumanbehavior |