Argumentation in artificial intelligence

Description

This volume is a systematic, expansive presentation of the major achievements in the intersection between two fields of inquiry: Argumentation Theory and Artificial Intelligence. Contributions from international researchers who have helped shape this dynamic area offer a progressive development of intuitions, ideas and techniques, from philosophical backgrounds, to abstract argument systems, to computing arguments, to the appearance of applications producing innovative results. Each chapter features extensive examples to ensure that readers develop the right intuitions before they move from one topic to another. In particular, the book exhibits an overview of key concepts in Argumentation Theory and of formal models of Argumentation in AI. After laying a strong foundation by covering the fundamentals of argumentation and formal argument modeling, the book expands its focus to more specialized topics, such as algorithmic issues, argumentation in multi-agent systems, and strategic aspects of argumentation. Finally, as a coda, the book explores some practical applications of argumentation in AI and applications of AI in argumentation. Argumentation in Artificial Intelligence is sure to become an essential resource for graduate students and researchers working in Autonomous Agents, AI and Law, Logic in Computer Science, Electronic Governance, and Multi-agent Systems. The book is suitable both as a comprehensive introduction to the field, and also as a highly organized and accessible reference for established researchers.  Read more... Abstract: This volume is a systematic, expansive presentation of the major achievements in the intersection between two fields of inquiry: Argumentation Theory and Artificial Intelligence. Contributions from international researchers who have helped shape this dynamic area offer a progressive development of intuitions, ideas and techniques, from philosophical backgrounds, to abstract argument systems, to computing arguments, to the appearance of applications producing innovative results. Each chapter features extensive examples to ensure that readers develop the right intuitions before they move from one topic to another. In particular, the book exhibits an overview of key concepts in Argumentation Theory and of formal models of Argumentation in AI. After laying a strong foundation by covering the fundamentals of argumentation and formal argument modeling, the book expands its focus to more specialized topics, such as algorithmic issues, argumentation in multi-agent systems, and strategic aspects of argumentation. Finally, as a coda, the book explores some practical applications of argumentation in AI and applications of AI in argumentation. Argumentation in Artificial Intelligence is sure to become an essential resource for graduate students and researchers working in Autonomous Agents, AI and Law, Logic in Computer Science, Electronic Governance, and Multi-agent Systems. The book is suitable both as a comprehensive introduction to the field, and also as a highly organized and accessible reference for established researchers Content: Abstract Argument Systems -- Semantics of Abstract Argument Systems -- Abstract Argumentation and Values -- Bipolar abstract argumentation systems -- Complexity of Abstract Argumentation -- Proof Theories and Algorithms for Abstract Argumentation Frameworks -- Argumentation Theory: A Very Short Introduction -- Arguments with Structure -- Argumentation Based on Classical Logic -- Argument-based Logic Programming -- A Recursive Semantics for Defeasible Reasoning -- Assumption-Based Argumentation -- The Toulmin Argument Model in Artificial Intelligence -- Proof Burdens and Standards -- Argumentation in Multi-Agent Systems -- Dialogue Games for Agent Argumentation -- Models of Persuasion Dialogue -- Argumentation for Decision Making -- Argumentation and Game Theory -- Belief Revision and Argumentation Theory -- Applications -- Argumentation in Legal Reasoning -- The Argument Interchange Format -- Empowering Recommendation Technologies Through Argumentation -- Arguing on the Semantic Grid -- Towards Probabilistic Argumentation -- Argument-Based Machine Learning.