Evaluating Explanations
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Evaluating Explanations
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.
Evaluating Explanations
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.
Evaluating, Doing and Writing Research in Psychology
Evaluating, Doing and Writing Research in Psychology is a thoroughly revised and expanded co-edition of the highly regarded Reasoning and Argument in Psychology, originally published by UNSW Press, Australia. It represents a comprehensive textbook for all undergraduates in psychology who need to undertake empirical research, taking them step-by-step through the process. In particular, it offers the a range of study skills enabling the student to understand the complex processes involved with psychological research, not really covered in other texts. Coverage includes: · A guide to evaluating statements, arguments and a range of different psychological explanations · Chapters on the interpretation and evaluation of data and evidence, understanding weaknesses in psychological argument, and measurement and numerical reasoning · Chapters on doing a literature review, writing up essays and projects, and reporting observational studies. This is a practical textbook. Textboxes are included to help students comprehend jargon, key research terms and likely problem areas in psychological research.At the end of each chapter, summaries, questions and exercises are included - all designed to give students extra clarification of issues and to help with their overall understanding. Plenty of new examples have been added from the previous edition and exercises are more clearly focused.