| Texto completo | |
| Autor(es): |
de Bona, Glauber
;
Nascimento Rocha, Victor Hugo
;
Cozman, Fabio Gagliardi
;
Cano, A
;
DeBock, J
;
Miranda, E
;
Moral, S
Número total de Autores: 7
|
| Tipo de documento: | Artigo Científico |
| Fonte: | INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 162; v. 147, p. 10-pg., 2021-01-01. |
| Resumo | |
We extend epistemic graphs, a powerful representation language employed in argumentation theory, first, by allowing conditional probabilities in that language. We also offer a new way of interpreting the graph as a set of restrictions based on a selected semantics for the abstract argumentation frameworks. The resulting semantics for epistemic graphs are given by credal sets that we characterize through inequalities. We illustrate the main issues in our proposals by resorting to arguments related to climate change. (AU) | |
| Processo FAPESP: | 19/07665-4 - Centro de Inteligência Artificial |
| Beneficiário: | Fabio Gagliardi Cozman |
| Modalidade de apoio: | Auxílio à Pesquisa - Programa eScience e Data Science - Centros de Pesquisa Aplicada |