Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Argumentation in Artificial Intelligence
Argumentation is all around us. Letters to the Editor often make points of cons- tency, and “Why” is one of the most frequent questions in language, asking for r- sons behind behaviour. And argumentation is more than ‘reasoning’ in the recesses of single minds, since it crucially involves interaction. It cements the coordinated social behaviour that has allowed us, in small bands of not particularly physically impressive primates, to dominate the planet, from the mammoth hunt all the way up to organized science. This volume puts argumentation on the map in the eld of Arti cial Intelligence. This theme has been coming for a while, and some famous pioneers are chapter authors, but we c...
Computational Models of Argument
Argumentation, which has long been a topic of study in philosophy, has become a well-established aspect of computing science in the last 20 years. This book presents the proceedings of the fifth conference on Computational Models of Argument (COMMA), held in Pitlochry, Scotland in September 2014. Work on argumentation is broad, but the COMMA community is distinguished by virtue of its focus on the computational and mathematical aspects of the subject. This focus aims to ensure that methods are sound – that they identify arguments that are correct in some sense – and provide an unambiguous specification for implementation; producing programs that reason in the correct way and building systems capable of natural argument or of recognizing argument. The book contains 24 long papers and 18 short papers, and the 21 demonstrations presented at the conference are represented in the proceedings either by an extended abstract or by association with another paper. The book will be of interest to all those whose work involves argumentation as it relates to artificial intelligence.
Computational Models of Argument
Argumentation has traditionally been studied across a number of fields, notably philosophy, cognitive science, linguistics and jurisprudence. The study of computational models of argumentation is a more recent endeavor, bringing together researchers from traditional fields and computer science and engineering within a rich, interdisciplinary matrix. Computational models of argumentation have been identified and used since the 1980s, and more recently an important role for argumentation in leading to principled decisions has emerged in several settings. This book presents the proceedings of COMMA 2022 the 9th International Conference on Computational Models of Argument, held in Cardiff, Wales...
Computational Models of Argument
"The papers in this volume formed the programme of the 1st International Conference on Computational Models of Argument (COMMA), which was hosted by the Dept. of Computer Science of the University of Liverpool from Sept. 11th-12th, 2006."--Pref.
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. This book includes articles, which provide a snapshot of research questions in the area of computational models of argument.
Computational Models of Argument
In its classical form, the study of argumentation focuses on human-oriented uses of argument, such as whether an argument is legitimate or flawed, engagement in debate, or the rhetorical aspects of argumentation. In recent decades, however, the study of logic and computational models of argumentation has emerged as a growing sub-area of AI. This book presents the Seventh International Conference on Computational Models of Argument (COMMA’18), held in Warsaw, Poland, from 12 to 14 September 2018. Since its inception in 2006, the conference and its related activities have developed alongside the steady growth of interest in computational argumentation worldwide, and the selection of 25 full ...
Computational Models of Argument
The investigation of computational models of argument is a rich and fascinating interdisciplinary research field with two ultimate aims: the theoretical goal of understanding argumentation as a cognitive phenomenon by modeling it in computer programs, and the practical goal of supporting the development of computer-based systems able to engage in argumentation-related activities with human users or among themselves. The biennial International Conferences on Computational Models of Argument (COMMA) provide a dedicated forum for the presentation and discussion of the latest advancements in the field, and cover both basic research and innovative applications. This book presents the proceedings ...
Computational Models of Argument
The subject of argumentation has been studied since ancient times, but it has seen major innovations since the advent of the computer age. Software already exists which can create and evaluate arguments in high-stake situations, such as medical diagnosis and criminal investigation; formal systems can help us appreciate the role of the value judgments which underlie opposing positions; and it is even possible to enter into argumentative dialogues as if playing a computer game. This book presents the 28 full papers, 17 short papers and a number of system demonstrations, described in an extended abstract, from the 2012 biennial Computational Models of Argument (COMMA) conference, held in Vienna...
Symbolic and Quantitative Approaches to Reasoning with Uncertainty
This book constitutes the refereed proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2007, held in Hammammet, Tunisia, Oktober 31 - November 2, 2007. The 78 revised full papers presented together with 3 invited papers were carefully reviewed and selected from over hundret submissions for inclusion in the book. The papers are organized in topical sections on Bayesian networks, graphical models, learning causal networks, planning, causality and independence, preference modelling and decision, argumentation systems, inconsistency handling, belief revision and merging, belief functions, fuzzy models, many-valued logical systems, uncertainty logics, probabilistic reasoning, reasoning models under uncertainty, uncertainty measures, probabilistic classifiers, classification and clustering, and industrial applications.
