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|
01/01/2015 → 28/02/2018
Project: Academy of Finland: Other research funding
Rintanen, J. (2017). Schematic Invariants by Reduction to Ground Invariants. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) (pp. 3644-3650). (Proceedings of the AAAI Conference on Artificial Intelligence). AAAI.