Valerie M Hudson

Artificial Intelligence And International Politics (eBook, PDF)

• Format: PDF

Produktbeschreibung

This book focuses on the early stirrings of interest in artificial intelligence as a potentially useful method of political analysis. It examines three general areas of artificial intelligence: international interaction, decision making groups, and cognitive processes in international politics.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 422
• Erscheinungstermin: 30. August 2019
• Englisch
• ISBN-13: 9780429698897
• Artikelnr.: 57606538

Autorenporträt

Valerie M Hudson

Inhaltsangabe

Introduction 1. Artificial Intelligence and International Relations: An
Overview Part One: Conceptual Issues and Practical Concerns 2. Artificial
Intelligence and Intuitive Foreign Policy Decision-Makers Viewed as Limited
Information Processors: Some Conceptual Issues and Practical Concerns for
the Future 3. Steps Toward Artificial Intelligence: Rule-Based, Case-Based,
and Explanation-Based Models of Politics 4. Text Modeling for International
Politics: A Tourist's Guide to RELATUS 5. Reasoning and Intelligibility 6.
The Computational Modeling of Strategic Time Part Two: AI/IR Research:
International Events and Foreign Policy Decision Making 7. Pattern
Recognition of International Event Sequences: A Machine Learning Approach
8. Scripting International Power Dramas: A Model of Situational
Predisposition 9. UNCLESAM: The Application of a Rule-Based Model of U.S.
Foreign Policy Making 10. Modeling Foreign Policy Decision Making as
Knowledge-Based Reasoning 11. Decision Making and Development: A "Glass
Box" Approach to Representation Part Three: AI/IR Research: The Discourse
of Foreign Policy 12. The Expertise of the Senate Foreign Relations
Committee 13. Reproduction of Perception and Decision in the Early Cold War
14. Theoretical Categories and Data Construction in Computational Models of
Foreign Policy 15. Semantic Content Analysis: A New Methodology for the
RELATUS Natural Language Environment 16. Time Space: Representing
Historical Time for Efficient Event Retrieval