Abstract
Merge-and-shrink heuristics crucially rely on effective reduction techniques, such as bisimulation-based shrinking, to avoid the combinatorial explosion of abstractions. We propose the concept of factored symmetries for merge-andshrink abstractions based on the established concept of symmetry reduction for state-space search. We investigate under which conditions factored symmetry reduction yields perfect heuristics and discuss the relationship to bisimulation. We also devise practical merging strategies based on this concept and experimentally validate their utility.
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 |
Publisher | AI Access Foundation |
Pages | 3378-3385 |
Number of pages | 8 |
ISBN (Electronic) | 9781577357032 |
State | Published - 1 Jun 2015 |
Externally published | Yes |
Event | 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015 - Austin, United States Duration: 25 Jan 2015 → 30 Jan 2015 |
Publication series
Name | Proceedings of the National Conference on Artificial Intelligence |
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Volume | 5 |
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 | 25/01/15 → 30/01/15 |
Bibliographical note
Publisher Copyright:© Copyright 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.