Epistemic Graphs for Representing and Reasoning with Positive and Negative Influences of Arguments
arXiv:1802.07489 · doi:10.1016/j.artint.2020.103236
Abstract
This paper introduces epistemic graphs as a generalization of the epistemic approach to probabilistic argumentation. In these graphs, an argument can be believed or disbelieved up to a given degree, thus providing a more fine--grained alternative to the standard Dung's approaches when it comes to determining the status of a given argument. Furthermore, the flexibility of the epistemic approach allows us to both model the rationale behind the existing semantics as well as completely deviate from them when required. Epistemic graphs can model both attack and support as well as relations that are neither support nor attack. The way other arguments influence a given argument is expressed by the epistemic constraints that can restrict the belief we have in an argument with a varying degree of specificity. The fact that we can specify the rules under which arguments should be evaluated and we can include constraints between unrelated arguments permits the framework to be more context--sensitive. It also allows for better modelling of imperfect agents, which can be important in multi--agent applications.
References in corpus (4)
Cited by in corpus (5)
- Epistemic Graphs for Representing and Reasoning with Positive and Negative Influences of Arguments
- SMProbLog: Stable Model Semantics in ProbLog and its Applications in Argumentation
- Polynomial-time Updates of Epistemic States in a Fragment of Probabilistic Epistemic Argumentation (Technical Report)
- Explainable Automated Reasoning in Law using Probabilistic Epistemic Argumentation
- Towards Ranking-based Semantics for Abstract Argumentation using Conditional Logic Semantics