Abstract
Computational models of argument aim at engaging argumentation-related activities with human users. In the present work we propose a new generalized version of abstract argument system, called Trust-affected Bipolar Weighted Argumentation Framework (T-BWAF). In this framework, two mainly interacting components are exploited to reason about the acceptability of arguments. The former is the BWAF, which combines and extends the theoretical models and properties of bipolar and weighted Argumentation Frameworks. The latter is the Trust Users Graph, which allow us to quantify gradual pieces of information regarding the source (who is the origin) of an argument. The synergy between them allow us to consider further gradual information which lead to a definition of intrinsic strength of an argument. For this reason, the evaluation of arguments for T-BWAF is defined under a ranking-based semantics, i.e. by assigning a numerical acceptability degree to each argument.
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Acknowledgments
This work was partially funded by the Italian PON 2007–2013 project PON02_00563_3489339 ‘Puglia@Service’.
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Pazienza, A., Ferilli, S., Esposito, F. (2017). On the Gradual Acceptability of Arguments in Bipolar Weighted Argumentation Frameworks with Degrees of Trust. In: Kryszkiewicz, M., Appice, A., Ślęzak, D., Rybinski, H., Skowron, A., Raś, Z. (eds) Foundations of Intelligent Systems. ISMIS 2017. Lecture Notes in Computer Science(), vol 10352. Springer, Cham. https://doi.org/10.1007/978-3-319-60438-1_20
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