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Evaluating Explanations: A Content Theory [NOOK Book]

Overview

Psychology and philosophy have long studied the nature and role of explanation. More recently, artificial intelligence research has developed promising theories of how explanation facilitates learning and generalization. By using explanations to guide learning, explanation-based methods allow reliable learning of new concepts in complex situations, often from observing a single example.

The author of this volume, however, argues that ...
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Evaluating Explanations: A Content Theory

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Overview

Psychology and philosophy have long studied the nature and role of explanation. More recently, artificial intelligence research has developed promising theories of how explanation facilitates learning and generalization. By using explanations to guide learning, explanation-based methods allow reliable learning of new concepts in complex situations, often from observing a single example.

The author of this volume, however, argues that explanation-based learning research has neglected key issues in explanation construction and evaluation. By examining the issues in the context of a story understanding system that explains novel events in news stories, the author shows that the standard assumptions do not apply to complex real-world domains. An alternative theory is presented, one that demonstrates that context -- involving both explainer beliefs and goals -- is crucial in deciding an explanation's goodness and that a theory of the possible contexts can be used to determine which explanations are appropriate. This important view is demonstrated with examples of the performance of ACCEPTER, a computer system for story understanding, anomaly detection, and explanation evaluation.
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Product Details

  • ISBN-13: 9781317782445
  • Publisher: Taylor & Francis
  • Publication date: 2/25/2014
  • Series: Artificial Intelligence Series
  • Sold by: Barnes & Noble
  • Format: eBook
  • Pages: 280
  • File size: 3 MB

Table of Contents

Acknowledgments
Overview and Reader's Guide
1 Explanation and Understanding 1
1.1 Fashioning Beliefs 1
1.2 Maintaining Beliefs During Understanding 4
1.3 Routine Understanding 5
1.4 Detecting Anomalies 6
1.5 Learning by Explaining Anomalies 10
1.6 What Is a Good Explanation? 12
1.7 Constructing Explanations 15
1.8 Implementing the Theory 16
1.9 Significance for Explanation-Based Systems 27
1.10 The Following Chapters 29
2 Perspective on the Theory 31
2.1 The SWALE Project 32
2.2 ACCEPTER Overview and Sample Run 36
2.9 Comparison to Views from AI 53
2.4 Comparison to Views from Psychology 66
2.5 Comparison to Views from Philosophy 67
2.6 Summary 69
3 Anomalies and Routine Understanding 71
3.1 The Nature of Anomalies 71
3.2 ACCEPTER's Routine Understanding 72
3.3 Overview of ACCEPTER's Anomaly Detection 84
3.4 Conflicts with Specific Prior Expectations 84
3.5 The Need for Additional Tests 90
4 Pattern-Based Anomaly Detection 91
4.1 Overview of ACCEPTER's Pattern Types 92
4.2 ACCEPTER's Patterns and their Structure 94
4.3 Pattern Retrieval 106
4.4 The Need to Identify Underlying Problems 107
4.5 Finer Grained Checks 109
4.6 What ACCEPTER's Checks Miss 118
4.7 Judging ACCEPTER's Anomaly Detection 121
4.8 Summary 122
5 Anomaly Characterization 125
5.1 From Detection to Characterization 125
5.2 The Information Characterizations Include 126
5.3 How Characterization Guides Search 128
5.4 Mapping Conflicts to Characterizations 132
5.5 Defining the Content of Anomaly Categories 135
6 A Vocabulary for Anomalies 137
6.1 Overview of the Categories 138
6.2 SURPRISING-PLAN-CHOICE 143
6.3 SURPRISING-PROP-CHOICE 150
6.4 Conclusion 152
7 Nonmotivational Anomaly Types 153
7.1 Overview of Nonmotivational Anomalies 153
7.2 PLAN-EXECUTION-FAILURE 154
7.3 BLOCKAGE-VIOLATION 160
7.4 PROCESS-EXECUTION-FAILURE 162
7.5 DEVICE-FAILURE 164
7.6 INFORMATION-FAILURE 165
7.7 UNUSUAL-FEATURE 166
7.8 FEATURE-DURATION-FAILURE 167
7.9 Judging the Vocabulary 168
7.10 Conclusion 171
8 Evaluating Relevance and Plausibility 173
8.1 Accounting for Surprising Features 174
8.2 Accounting for Why Expectations Failed 180
8.3 Evaluating Plausibility 185
8.4 Conclusion 193
9 Focusing on Important Factors 195
9.1 Each Anomaly Has Many Explanations 195
9.2 How Goals Affect Explanation 196
9.3 Major Explanation Purposes 199
9.4 How Explanation Purposes Arise 200
9.5 How Goals Affect ACCEPTER's Evaluation 203
9.6 Explaining to Predict 204
9.7 Explaining for Repair 214
9.8 Explaining for Control 218
9.9 Explaining to Assign Praise or Blame 224
9.10 Sketch of Requirements for Other Goals 226
9.11 Summary of Evaluation Dimensions 228
9.12 Goal-Based Adaptation 230
9.13 Conclusion 230
10 Conclusions and Future Directions 233
10.1 Summary and Significance of the Theory 233
10.2 Future Directions 235
10.3 Final Notes 239
References 241
Author Index 253
Subject Index 255
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