Projects per year
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.
|Title of host publication||Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)|
|Number of pages||7|
|Publication status||Published - 2017|
|MoE publication type||A4 Article in a conference publication|
|Event||AAAI Conference on Artificial Intelligence - San Francisco, United States|
Duration: 4 Feb 2017 → 9 Feb 2017
Conference number: 31
|Name||Proceedings of the AAAI Conference on Artificial Intelligence|
|Conference||AAAI Conference on Artificial Intelligence|
|Period||04/02/2017 → 09/02/2017|
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- 1 Finished
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.
01/01/2015 → 31/12/2017
Project: Academy of Finland: Other research funding