Abstract
Modularity is an essential aspect of knowledge representation theory and practice. It has received substantial attention. We introduce model-based modular systems, an abstract framework for modular knowledge representation formalisms, similar in scope to multi-context systems but employing a simpler information-flow mechanism. We establish the precise relationship between the two frameworks, showing that they can simulate each other. We demonstrate that recently introduced modular knowledge representation formalisms integrating logic programming with satisfiability and, more generally, with constraint satisfaction can be cast as modular systems in our sense. These results show that our formalism offers a simple unifying framework for studies of modularity in knowledge representation.
| Original language | English |
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| Title of host publication | Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015 |
| Pages | 1532-1538 |
| Number of pages | 7 |
| ISBN (Electronic) | 9781577357001 |
| State | Published - Jun 1 2015 |
| Event | 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015 - Austin, United States Duration: Jan 25 2015 → Jan 30 2015 |
Publication series
| Name | Proceedings of the National Conference on Artificial Intelligence |
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| Volume | 2 |
Conference
| Conference | 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015 |
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| Country/Territory | United States |
| City | Austin |
| Period | 1/25/15 → 1/30/15 |
Bibliographical note
Publisher Copyright:Copyright © 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
ASJC Scopus subject areas
- Software
- Artificial Intelligence