This book uses a computational social science approach to analyze government formation and survival in parliamentary democracies. It models 'functionally rational' politicians who attack complex problems using heuristics and also develops artificial intelligence algorithms which relentlessly learn how best to 'win' the political game.
This book uses a computational social science approach to analyze government formation and survival in parliamentary democracies. It models 'functionally rational' politicians who attack complex problems using heuristics and also develops artificial intelligence algorithms which relentlessly learn how best to 'win' the political game.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Scott de Marchi is Professor of Political Science and Director of Decision Science at Duke University. He is a principal investigator for the for the National Science Foundation's Empirical Implications of Theoretical Models program and his research focuses on decision-making in contexts that include Congress, coalition and crisis bargaining, and interstate conflict.
Inhaltsangabe
Introduction 1. Governance, complexity, computation and rationality 2. The governance cycle 3. Agent based model of government formation and survival 4. Artificial intelligence and government formation 5. Analyzing models of government formation and survival 6. The empirics of government formation and survival 7. Conclusions and aspirations Appendices.
Introduction 1. Governance, complexity, computation and rationality 2. The governance cycle 3. Agent based model of government formation and survival 4. Artificial intelligence and government formation 5. Analyzing models of government formation and survival 6. The empirics of government formation and survival 7. Conclusions and aspirations Appendices.
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