Schematic Invariants by Reduction to Ground Invariants

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

39 Downloads (Pure)


Computation of invariants, which are approximate reachability information for state-space search problems such as AI planning, has been considered to be more scalable when using a schematic representation of actions/events rather than an instantiated/ground representation. A disadvantage of schematic algorithms, however, is their complexity, which also leads to high runtimes when the number of schematic events/actions is high. We propose algorithms that reduce the problem of finding schematic invariants to solving a smaller ground problem.
Original languageEnglish
Title of host publicationProceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)
Number of pages7
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventAAAI Conference on Artificial Intelligence - San Francisco, United States
Duration: 4 Feb 20179 Feb 2017
Conference number: 31

Publication series

NameProceedings of the AAAI Conference on Artificial Intelligence
ISSN (Print)2159-5399
ISSN (Electronic)2374-3468


ConferenceAAAI Conference on Artificial Intelligence
Abbreviated titleAAAI
Country/TerritoryUnited States
CitySan Francisco


Dive into the research topics of 'Schematic Invariants by Reduction to Ground Invariants'. Together they form a unique fingerprint.
  • Finnish centre of excellence in computational inference research

    Xu, Y., Rintanen, J., Kaski, S., Anwer, R., Parviainen, P., Soare, M., Vuollekoski, H., Rezazadegan Tavakoli, H., Peltola, T., Blomstedt, P., Puranen, S., Dutta, R., Gebser, M., Mononen, T., Bogaerts, B., Tasharrofi, S., Pesonen, H., Weinzierl, A. & Yang, Z.


    Project: Academy of Finland: Other research funding

Cite this