Evaluation Techniques and Systems for Answer Set Programming: a Survey-Reference-Cited by-同舟云学术

Evaluation Techniques and Systems for Answer Set Programming: a Survey

Published:2018-07 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
language:
Short-container-title:

Author:

Gebser Martin¹,Leone Nicola²,Maratea Marco³,Perri Simona²,Ricca Francesco²,Schaub Torsten¹

Affiliation:

1. University of Potsdam, Germany

2. University of Calabria, Italy

3. University of Genova, Italy

Abstract

Answer set programming (ASP) is a prominent knowledge representation and reasoning paradigm that found both industrial and scientific applications. The success of ASP is due to the combination of two factors: a rich modeling language and the availability of efficient ASP implementations. In this paper we trace the history of ASP systems, describing the key evaluation techniques and their implementation in actual tools.

Publisher

International Joint Conferences on Artificial Intelligence Organization

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Efficient Solver for ASP(Q);Theory and Practice of Logic Programming;2023-07

2. Symbolic Artificial Intelligence Methods for Prescriptive Analytics;Digital Transformation;2023

3. Forget and Regeneration Techniques for Optimizing ASP-Based Stream Reasoning;Practical Aspects of Declarative Languages;2023

4. Knowledge-Based Artificial Intelligence;Encyclopedia of Data Science and Machine Learning;2022-10-14

5. ASP-based Multi-shot Reasoning via DLV2 with Incremental Grounding;Proceedings of the 24th International Symposium on Principles and Practice of Declarative Programming;2022-09-20