Algorithms and Arguments: The Foundational Role of the ATAI-question (original) (raw)
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Encyclopedia of Information Ethics and Security
Argumentation is usually thought of as a domain within philosophy, or rhetoric. Yet, it has made inroads in the works of computer scientists, especially, yet not only, the logistics among them. Information Ethics and Security, in the title of this encyclopedia, respectively belong in ethics (in general) and in the forensic sciences (security is both preventative and about discovering traces of perpetrators). Deontic logic?that is, logic for representing obligations and permissions (Åqvist, 2002; Abrahams & Bacon, 2002) being used, for example in databases or in security?has been an early (1970s) and conspicuous stream within “AI & Law,” a domain in which models of argumentation have featured prominently since the 1990s (e.g., Ashley, 1990; Prakken & Sartor, 1996).
Argumentation in artificial intelligence
Artificial Intelligence, 2007
Over the last ten years, argumentation has come to be increasingly central as a core study within Artificial Intelligence (AI). The articles forming this volume reflect a variety of important trends, developments, and applications covering a range of current topics relating to the theory and applications of argumentation. Our aims in this introduction are, firstly, to place these contributions in the context of the historical foundations of argumentation in AI and, subsequently, to discuss a number of themes that have emerged in recent years resulting in a significant broadening of the areas in which argumentation based methods are used. We begin by presenting a brief overview of the issues of interest within the classical study of argumentation: in particular, its relationshipin terms of both similarities and important differences-to traditional concepts of logical reasoning and mathematical proof. We continue by outlining how a number of foundational contributions provided the basis for the formulation of argumentation models and their promotion in AI related settings and then consider a number of new themes that have emerged in recent years, many of which provide the principal topics of the research presented in this volume. We note that in a number of systems, consistency cannot be formally proven, cf.
Argumentation schemes in AI: A literature review. Introduction to the special issue
Argument & Computation, 2021
Argumentation schemes [35,80,91] are a relatively recent notion that continues an extremely ancient debate on one of the foundations of human reasoning, human comprehension, and obviously human argumentation, i.e., the topics. To understand the revolutionary nature of Walton's work on this subject matter, it is necessary to place it in the debate that it continues and contributes to, namely a view of logic that is much broader than the formalistic perspective that has been adopted from the 20th century until nowadays. With his book Argumentation schemes for presumptive reasoning, Walton attempted to start a dialogue between three different fields or views on human reasoning-one (argumentation theory) very recent, one (dialectics) very ancient and with a very long tradition, and one (formal logic) relatively recent, but dominating in philosophy. Argumentation schemes were proposed as dialectical instruments, in the sense that they represented arguments not only as formal relations, but also as pragmatic inferences, as they at the same time depend on what the interlocutors share and accept in a given dialogical circumstance, and affect their dialogical relation. In this introduction, the notion of argumentation scheme will be analyzed in detail, showing its different dimensions and its defining features which make them an extremely useful instrument in Artificial Intelligence. This theoretical background will be followed by a literature review on the uses of the schemes in computing, aimed at identifying the most important areas and trends, the most promising proposals, and the directions of future research.
Argumentation: Reconciling Human and Automated Reasoning
International Joint Conference on Artificial Intelligence, 2016
We study how using argumentation as an alternative foundation for logic gives a framework in which we can reconcile human and automated reasoning. We analyse this reconciliation between human and automated reasoning at three levels: (1) at the level of classical, strict reasoning on which, till today, automated reasoning and computing are based, (2) at the level of natural or ordinary human level reasoning as studied in cognitive psychology and which artificial intelligence, albeit in its early stages, is endeavouring to automate, and (3) at the level of the recently emerged cognitive computing paradigm where systems are required to be cognitively compatible with human reasoning based on common sense or expert knowledge, machine-learned from unstructured data in corpora over the web or other sources.
The Impact of Argumentation on Artificial Intelligence
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The research of the Amsterdam School has spread outward across the discipline of argumentation studies like a new day, awakening us to new vistas, casting light on new opportunities, and offering a fresh look at our familiar surroundings. Over the years this approach has proved so remarkably effective that many of its central tenets have been widely recognized and accepted.
Argumentation and dialogue in artificial intelligence
2005
In Artificial Intelligence reasoning is often modelled on the presentation of a proof. In some domains and for some topics this is entirely appropriate, but if we look at the justifications of reasoning offered in practice, they often fall short of the standards required by proof. Whereas a proof compels us to accept the conclusion if we accept the premises, natural language justifications tend to be open to objections: they may persuade, but they rarely compel.
Preface: Key Strategies to Address Argument and Computation
The problems lying at the intersection between argumentation theory and computer science constitute the subject of an intensive inquiry undertaken within the recent study of reasoning and argument. The label "Argument and Computation" characterizes the field of inquiry undertaken by the nascent research movement which has developed during the past decade. 1
An Axiomatic Account of Formal Argumentation
PROCEEDINGS OF THE NATIONAL …, 2005
Argumentation theory has become an important topic in the field of AI. The basic idea is to construct arguments in favor and against a statement, to select the “acceptable” ones and, finally, to determine whether the statement can be accepted or not. Dung’s elegant account of abstract argumentation (Dung 1995) may have caused some to believe that defining an argumentation formalism is simply a matter of determining how arguments and their defeat relation can be constructed from a given knowledge base. Unfortunately, things are not that simple; many straightforward instantiations of Dung’s theory can lead to very unintuitive results, as is discussed in this paper. In order to avoid such anomalies, in this paper we are interested in defining some rules, called rationality postulates or axioms, that govern the well definition of an argumentation system. In particular, we define two important rationality postulates that any system should satisfy: the consistency and the closedness of the results returned by that system. We then provide a relatively easy way in which these quality postulates can be warranted by our argumentation system.
Argumenta: Festschrift fur Manfred Kienpointner, ed. P. Anreiter, E. Mairhofer and C. Posch, Vienna, Praesens Verlag, 2015, 595-617.
Kienpointner (1997) showed how the ancient status theory and the Aristotelian theory of topics are parts of an art of argument invention that selects premises to be used in a chain of argumentation from a database of premises accepted by the audience a speaker is trying to persuade. He showed how pursuit of this art of finding arguments, although discredited in the Enlightenment, has recently has been taken up again by argumentation theorists. In this paper it is shown that with the recent advent of computational argumentation systems in artificial intelligence, a technology is now available to help an arguer to find arguments that support her claim, and to refute counter-arguments opposing her claim.