arXiv Open Access 2023

Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach

Michael Gelfond Jorge Fandinno Evgenii Balai

Lihat Sumber

Abstrak

This paper presents a rich knowledge representation language aimed at formalizing causal knowledge. This language is used for accurately and directly formalizing common benchmark examples from the literature of actual causality. A definition of cause is presented and used to analyze the actual causes of changes with respect to sequences of actions representing those examples.

Topik & Kata Kunci

cs.AI cs.LO

Penulis (3)

Michael Gelfond

Jorge Fandinno

Evgenii Balai

Format Sitasi

APA MLA BibTeX

Gelfond, M., Fandinno, J., Balai, E. (2023). Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach. https://arxiv.org/abs/2306.03874

Akses Cepat

Lihat di Sumber

Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓