@inproceedings{f2c7e5121a204a8aa856c86daa4d8e38,
title = "Towards a connectionist argumentation framework",
abstract = "While neural networks have been successfully used in a number of machine learning applications, logical languages have been the standard for the representation of legal and argumentative reasoning [6]. In this paper, we present a new hybrid model of computation that allows for the deduction and learning of argumentative reasoning. We do so by using Neural-Symbolic Learning Systems to translate argumentation networks into standard neural networks. The approach enables cummulative argumentation through learning, as the strength of the arguments change over time.",
author = "Garcez, {S. D.Avila} and Gabbay, {D. M.} and Lamb, {L. C.}",
year = "2004",
language = "אנגלית",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "987--988",
editor = "{de Mantaras}, {Ramon Lopez} and Lorenza Saitta",
booktitle = "ECAI 2004 - 16th European Conference on Artificial Intelligence, including Prestigious Applications of Intelligent Systems, PAIS 2004 - Proceedings",
address = "הולנד",
note = "16th European Conference on Artificial Intelligence, ECAI 2004 ; Conference date: 22-08-2004 Through 27-08-2004",
}