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