Bridging the Gap between Abstract Argumentation Systems and Logic

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A deductive argument is a pair where the first item is a set of premises, the second item is a claim, and the premises entail the claim. This can be formalised by assuming a logical language for the premises and the claim, and logical entailment (or consequence relation) for showing that the claim follows from the premises. Examples of logics that can be used include classical logic, modal logic, description logic, temporal logic, and conditional logic. A counterargument for an argument A is an argument B where the claim of B contradicts the premises of A. Different choices of logic, and different choices for the precise definitions of argument and counterargument, give us a range of possibilities for formalising deductive argumentation. Further options are available to us for choosing the arguments and counterarguments we put into an argument graph. If we are to construct an argument graph based on the arguments that can be constructed from a knowledgebase, then we can be exhaustive in including all arguments and counterarguments that can be constructed from the knowledgebase. But there are other options available to us. We consider some of the possibilities in this review.

Section: Properties Of Exhaustive Argument Graphsmentioning

confidence: 99%

Constructing argument graphs with deductive arguments: a tutorial

Besnard¹,

Hunter²

2014

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“…Some of them, like the well-known rebutting, are symmetric. However, it was shown in Amgoud and Besnard (2009) that any argumentation framework which is grounded on a Tarskian logic Tarski (1956) and uses a symmetric attack relation may violate the rationality postulates proposed in Caminada and Amgoud (2007), namely the one on consistency. Indeed, such a framework may have an extension which supports inconsistent conclusions.…”

Section: Binary Trust Supported By Argumentsmentioning

confidence: 99%

An argumentation-based approach for reasoning about trust in information sources

Amgoud¹,

Demolombe²

2014

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During a dialogue, agents exchange information with each other and need thus to deal with incoming information. For that purpose, they should be able to reason effectively about trustworthiness of information sources. This paper proposes an argument-based system that allows an agent to reason about its own beliefs and information received from other sources. An agent's beliefs are of two kinds: beliefs about the environment (like the window is closed) and beliefs about trusting sources (like agent i trusts agent j). Six basic forms of trust are discussed in the paper including the most common one on sincerity. Starting with a base which contains such information, the system builds two types of arguments: arguments in favour of trusting a given source of information and arguments in favour of believing statements which may be received from other agents. We discuss how the different arguments interact and how an agent may decide to trust another source and thus to accept information coming from that source. The system is then extended in order to deal with graded trust (like agent i trusts to some extent agent j).

“…Nowadays, however, there is a growing body of work that models argumentation as inconsistency handling in either classical logic or some other standard deductive logic Hunter 2001, 2008;Amgoud and Cayrol 2002;Parsons, Wooldridge, and Amgoud 2003;Amgoud and Besnard 2009;Gorogiannis and Hunter 2011). In Pollock's terms, this work regards all reasons as deductive.…”

Section: A Critique Of Current Computational Models Of Argument In LImentioning

confidence: 99%

An appreciation of John Pollock's work on the computational study of argument

Prakken

Horty

2012

) was an influential American philosopher who made important contributions to various fields, including epistemology and cognitive science. In the last 25 years of his life, he also contributed to the computational study of defeasible reasoning and practical cognition in artificial intelligence. He developed one of the first formal systems for argumentation-based inference and he put many issues on the research agenda that are still relevant for the argumentation community today. This paper presents an appreciation of Pollock's work on defeasible reasoning and its relevance for the computational study of argument. In our opinion, Pollock deserves to be remembered as one of the founding fathers of the field of computational argument, while, moreover, his work contains important lessons for current research in this field, reminding us of the richness of its object of study.