Representing and applying knowledge for argumentation in a social context |
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Authors: | Chris Reed |
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Affiliation: | (1) Department of Information Systems and Computing, Brunel University, UB8 3PH Uxbridge, Middlesex, UK |
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Abstract: | The concept of argumentation in AI is based almost exclusively on the use of formal, abstract representations. Despite their appealing computational properties, these abstractions become increasingly divorced from their real world counterparts, and, crucially, lose the ability to express the rich gamut of natural argument forms required for creating effective text. In this paper, the demands that socially situated argumentation places on knowledge representation are explored, and the various problems with existing formalisations are discussed. Insights from argumentation theory and social psychology are then adduced as key contributions to a notion of social context which is both computationally tractable and suitably expressive for handling the complexities of argumentation found in natural language. |
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Keywords: | Argumentation Natural language generation Persuasion User modelling |
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