| Full text | |
| Author(s): |
de Bona, Glauber
;
Nascimento Rocha, Victor Hugo
;
Cozman, Fabio Gagliardi
;
Cano, A
;
DeBock, J
;
Miranda, E
;
Moral, S
Total Authors: 7
|
| Document type: | Journal article |
| Source: | INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 162; v. 147, p. 10-pg., 2021-01-01. |
| Abstract | |
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) | |
| FAPESP's process: | 19/07665-4 - Center for Artificial Intelligence |
| Grantee: | Fabio Gagliardi Cozman |
| Support Opportunities: | Research Grants - Research Program in eScience and Data Science - Research Centers in Engineering Program |