Use of argumentation methods applied to legal reasoning is a relatively new field of study. The book provides a survey of the leading problems, and outlines how future research using argumentation-based methods show great promise of leading to useful solutions. The problems studied include not only these of argument evaluation and argument invention, but also analysis of specific kinds of evidence commonly used in law, like witness testimony, circumstantial evidence, forensic evidence and character evidence. New tools for analyzing these kinds of evidence are introduced.

Recent work in artificial intelligence has increasingly turned to argumentation as a rich, interdisciplinary area of research that can provide new methods related to evidence and reasoning in the area of law. Douglas Walton provides an introduction to basic concepts, tools and methods in argumentation theory and artificial intelligence as applied to the analysis and evaluation of witness testimony. He shows how witness testimony is by its nature inherently fallible and sometimes subject to disastrous failures. At the same time such testimony can provide evidence that is not only necessary but inherently reasonable for logically guiding legal experts to accept or reject a claim. Walton shows how to overcome the traditional disdain for witness testimony as a type of evidence shown by logical positivists, and the views of trial sceptics who doubt that trial rules deal with witness testimony in a way that yields a rational decision-making process.

Use of argumentation methods applied to legal reasoning is a relatively new field of study. The book provides a survey of the leading problems, and outlines how future research using argumentation-based methods show great promise of leading to useful solutions. The problems studied include not only these of argument evaluation and argument invention, but also analysis of specific kinds of evidence commonly used in law, like witness testimony, circumstantial evidence, forensic evidence and character evidence. New tools for analyzing these kinds of evidence are introduced.

A leading expert in informal logic, Douglas Walton turns his attention in this new book to how reasoning operates in trials and other legal contexts, with special emphasis on the law of evidence. The new model he develops, drawing on methods of argumentation theory that are gaining wide acceptance in computing fields like artificial intelligence, can be used to identify, analyze, and evaluate specific types of legal argument. In contrast with approaches that rely on deductive and inductive logic and rule out many common types of argument as fallacious, Walton&’s aim is to provide a more expansive view of what can be considered &"reasonable&" in legal argument when it is construed as a dynamic, rule-governed, and goal-directed conversation. This dialogical model gives new meaning to the key notions of relevance and probative weight, with the latter analyzed in terms of pragmatic criteria for what constitutes plausible evidence rather than truth.

This book, written by a leading expert, and based on the latest research, shows how to apply methods of argumentation to a range of examples.

This book describes how text analytics and computational models of legal reasoning will improve legal IR and let computers help humans solve legal problems.

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 can now see a broader systematic area emerging in the sum of topics and results. As a logician, I nd this intriguing, since I see AI as ‘logic continued by other means’, reminding us of broader views of what my discipline is about. Logic arose originally out of re ection on many-agent practices of disputation, in Greek Ant- uity, but also in India and China. And logicians like me would like to return to this broader agenda of rational agency and intelligent interaction. Of course, Aristotle also gave us a formal systems methodology that deeply in uenced the eld, and eventually connected up happily with mathematical proof and foundations.