Anthony Hunter

Philippe Besnard

Sylvie Doutre

This volume of Computational Models of Argument focuses on the aim to develop software tools to assist users in constructing and evaluating arguments and counterarguments and/or to develop automated systems for constructing and evaluating arguments and counterarguments. Some articles provide a valuable snapshot of the leading research questions in the area of computational models of argument, others draw on the wealth of research on the philosophical questions surrounding the notions arising in argumentation, or address knowledge representation and reasoning issues emerging from modeling argumentation. They also consider appropriate models of wider rhetorical issues arising in argumentation and propose and evaluate algorithmic solutions associated with generating and judging constellations of arguments. Included are articles proposing standards for exchanging information associated with argumentation so that different systems can work together. In addition, some articles report practical working tools for computational argumentation.

Proceedings of COMMA 2008

Computational Models of Argument

Steve Hanks

Proceedings of the Eleventh Conference (1995) : August 18-20, 1995

Uncertainty in Artificial Intelligence

Salem Benferhat

This book constitutes the refereed proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2001, held in Toulouse, France in September 2001. The 68 revised full papers presented together with three invited papers were carefully reviewed and selected from over a hundred submissions. The book offers topical sections on decision theory, partially observable Markov decision processes, decision-making, coherent probabilities, Bayesian networks, learning causal networks, graphical representation of uncertainty, imprecise probabilities, belief functions, fuzzy sets and rough sets, possibility theory, merging, belief revision and preferences, inconsistency handling, default logic, logic programming, etc.

6th European Conference, ECSQARU 2001, Toulouse, France, September 19-21, 2001. Proceedings

Symbolic and Quantitative Approaches to Reasoning with Uncertainty

This book is written for those who are interested in a fonnalization of human reasoning, especially in order to build "intelligent" computer systems. Thus, it is mainly designed for the Artificial Intelligence community, both students and researchers, although it can be useful for people working in related fields like cognitive psychology. The major theme is not Artificial Intelligence applications, although these are discussed throughout in sketch fonn. Rather, the book places a heavy emphasis on the fonnal development of default logic, results and problems. Default logic provides a fonnalism for an important part of human reasoning. Default logic is specifically concerned with common sense reasoning, which has recently been recognized in the Artificial Intelligence literature to be of fundamental importance for knowledge representation. Previously, fonnalized reasoning systems failed in real world environments, though succeeding with an acceptable ratio in well-defined environments. This situation enabled empirical explorations and the design of systems without theoretical justification. In particular, they could not be compared since there was no basis to judge their respective merits. Default logic turned out to be very fruitful by proving the correctness of some of them. We hope that this book will initiate other successful developments in default logic.

Philippe Besnard

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