Abstract
A novel approach to argumentation has been started by A. Garcez et al. Inspired by their work, we further go on investigating it, but turn to a more syncretic direction such as the interplay between neural net argumentation and symbolic argumentation. This paper is a sequel to our former one (Part I) [1]. In this paper we address ourselves to the following basic questions that can not be overlooked.
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Can the neural argumentation algorithm compute the fixpoint semantics for formal argumentation?
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Can argumentative dialogues be extracted from the neural net argumentation?
Consequently, we give the positive answers to them. They are beneficial for understanding or characterizing the computation power and outcome of the neural net argumentation from the perspective of the symbolic argumentation. We also exemplify these results.
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Makiguchi, W., Sawamura, H. (2008). A Hybrid Argumentation of Symbolic and Neural Net Argumentation (Part II). In: Rahwan, I., Parsons, S., Reed, C. (eds) Argumentation in Multi-Agent Systems. ArgMAS 2007. Lecture Notes in Computer Science(), vol 4946. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78915-4_14
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DOI: https://doi.org/10.1007/978-3-540-78915-4_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78914-7
Online ISBN: 978-3-540-78915-4
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