Causal Learning (eBook)

Advances in Research and Theory

eBook Download: PDF

1996 | 1. Auflage
442 Seiten
Elsevier Science (Verlag)
978-0-08-086385-6 (ISBN)

Infos

The Psychology of Learning and Motivation publishes empirical and theoretical contributions in cognitive and experimental psychology, ranging from classical and instrumental conditions to complex learning and problem solving. This guest-edited special volume is devoted to current research and discussion on associative versus cognitive accounts of learning. Written by major investigators in the field, topics include all aspects of causal learning in an open forum in which different approaches are brought together.

Key Features
* Up-to-date review of the literature
* Discusses recent controversies
* Presents major advances in understanding causal learning
* Synthesizes contrasting approaches
* Includes important empirical contributions
* Written by leading researchers in the field

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The Psychology of Learning and Motivation publishes empirical and theoretical contributions in cognitive and experimental psychology, ranging from classical and instrumental conditions to complex learning and problem solving. This guest-edited special volume is devoted to current research and discussion on associative versus cognitive accounts of learning. Written by major investigators in the field, topics include all aspects of causal learning in an open forum in which different approaches are brought together. - Up-to-date review of the literature- Discusses recent controversies- Presents major advances in understanding causal learning- Synthesizes contrasting approaches- Includes important empirical contributions- Written by leading researchers in the field

Inhalt

Front Cover 1
Causal Learning 4
Copyright Page 5
Contents 6
Contributors 10
Praface 12
CHAPTER 1. ASSOCIATIVE AND NORMATIVE MODELS OF CAUSAL INDUCTION: REACTING TO VERSUS UNDERSTANDING CAUSE 14
I. Two Models for Causal Reasoning 14
II. Some Empirical Work 20
III. Some Concluding Comments 46
References 54
CHAPTER 2. KNOWLEDGE-BASED CAUSAL INDUCTION 60
I. Introduction 60
II. The Associative View 60
III. Causal-Model Theory 64
IV. Conclusion 95
References 97
CHAPTER 3. A COMPARATIVE ANALYSIS OF NEGATIVE CONTINGENCY LEARNING IN HUMANS AND NONHUMANS 102
I. Introduction 102
II. Paradigms of Study 106
III. Points of Correspondence 110
IV. Mechanisms 124
V. Conclusions 137
References 138
CHAPTER 4. ANIMAL ANALOGUES OF CAUSAL JUDGMENT 146
I. Introduction 146
II. Are Animals Capable of Causal Judgments? 146
III. The Problem of Prior Knowledge and the Benefit of Animal Subjects 148
IV. Problems with Verbal Assessment of Causal Judgment 150
V. Behavioral Assessment of Causal Judgment 151
VI. Different Types of Behavioral Assessment 152
VII. Causal Training: Verbal, Pavlovian, and Instrumental Procedures 154
VIII. Trial Order: Backward Blocking as a Discrepancy between Causal Learning in Humans and Conditioning in Animals 156
IX. Cue Competition between Effects as Well as between Causes 167
X. Temporal Priority 172
XI. Conclusions 174
References 175
CHAPTER 5. CONDITIONALIZING CAUSALITY 180
I. Introduction 180
II. Conditional versus Unconditional Contingencies 181
III. Mathematical Properties of Contingencies with Two Potential Causes 191
IV. “Post-dictions” and Predictions of the Conditional Contingency Analysis 195
V. Limitations of the Conditional Contingency Analysis 204
VI. Conditionalizing as a General Procedure in Causal Attribution 209
VII. Summary 215
References 217
CHAPTER 6. CAUSATION AND ASSOCIATION 220
I. Comparing Information Integration Theory with Associative Learning Theory 221
II. Tracking Causal Rating over Changing Interevent Relations 240
III. Judging the Causal Efficacy of Nonpresented Stimuli 252
IV. Competition among Uncorrelated Cues 269
V. Concluding Comments 273
References 274
CHAPTER 7. DISTINGUISHING ASSOCIATIVE AND PROBABILISTIC CONTRAST THEORIES OF HUMAN CONTINGENCY JUDGMENT 278
I. Introduction 278
II. Convergence in Noncontingent Conditions 286
III. Causal Models and Causal Order 293
IV. Retrospective Revaluation 297
V. Trial Order Effects 304
VI. Configural Representations 312
VII. Conclusions 317
References 320
CHAPTER 8. A CAUSAL-POWER THEORY OF FOCAL SETS 326
I. Introduction 326
II. Empirical Tests of the Power PC Theory 339
III. Implications for the Rescorla–Wagner Model 353
IV. Implications of the Power PC Theory 359
References 366
CHAPTER 9. THE USE OF INTERVENING VARIABLES IN CAUSAL LEARNING 370
I. Evidence for Intervening Concept Learning 371
II. Intervening Concept Learning Model 378
III. Theoretical Results 387
IV. Prior Knowledge: New Experimental Work 392
V. Conclusions 401
References 404
CHAPTER 10. STRUCTURAL AND PROBABILISTIC CAUSALITY 406
I. Introduction 406
II. Probabilistic Causality 409
III. The Language of Causal Graphs 418
IV. Structural Causality 428
V. Conclusions 445
References 446
Index 450
Contents of Recent Volumes 452

Produkt-Details

• Erscheint lt. Verlag: 26.9.1996
• Mitarbeit: Herausgeber (Serie): Keith J. Holyoak, Douglas L. Medin, David R. Shanks
• Sprache: englisch
• Themenwelt: Geisteswissenschaften ► Psychologie ► Allgemeine Psychologie
• Themenwelt: Geisteswissenschaften ► Psychologie ► Biopsychologie / Neurowissenschaften
• Themenwelt: Geisteswissenschaften ► Psychologie ► Pädagogische Psychologie
• Themenwelt: Geisteswissenschaften ► Psychologie ► Sozialpsychologie
• Themenwelt: Geisteswissenschaften ► Psychologie ► Test in der Psychologie
• Themenwelt: Geisteswissenschaften ► Psychologie ► Verhaltenstherapie
• ISBN-10: 0-08-086385-X / 008086385X
• ISBN-13: 978-0-08-086385-6 / 9780080863856