Schematic Invariants by Reduction to Ground Invariants

Jussi Rintanen

Schematic Invariants by Reduction to Ground Invariants

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference contribution › Scientific › vertaisarvioitu

41 Lataukset (Pure)

Abstrakti

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.

Alkuperäiskieli	Englanti
Otsikko	Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)
Kustantaja	AAAI
Sivut	3644-3650
Sivumäärä	7
Tila	Julkaistu - 2017
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisuussa
Tapahtuma	AAAI Conference on Artificial Intelligence - San Francisco, Yhdysvallat Kesto: 4 helmik. 2017 → 9 helmik. 2017 Konferenssinumero: 31

Julkaisusarja

Nimi	Proceedings of the AAAI Conference on Artificial Intelligence
Kustantaja	AAAI
ISSN (painettu)	2159-5399
ISSN (elektroninen)	2374-3468

Conference

Conference	AAAI Conference on Artificial Intelligence
Lyhennettä	AAAI
Maa/Alue	Yhdysvallat
Kaupunki	San Francisco
Ajanjakso	04/02/2017 → 09/02/2017

Pääsy asiakirjaan

Rintanen17aaaiAccepted author manuscript, 232 KBLisenssi: Määrittelemätön

https://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14955

OpenUrl-saatavuus

Koko teksti

Suomalainen laskennallisen päättelyn huippuyksikkö
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
Projekti: Academy of Finland: Other research funding

Science-IT
Mikko Hakala (Manager)
Perustieteiden korkeakoulu
Laitteistot/tilat: Facility

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@inproceedings{229ef6707e4143dfb62c528e06e4b8dc,

title = "Schematic Invariants by Reduction to Ground Invariants",

abstract = "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.",

author = "Jussi Rintanen",

year = "2017",

language = "English",

series = "Proceedings of the AAAI Conference on Artificial Intelligence",

publisher = "AAAI",

pages = "3644--3650",

booktitle = "Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)",

address = "United States",

note = "AAAI Conference on Artificial Intelligence, AAAI ; Conference date: 04-02-2017 Through 09-02-2017",

}

Rintanen, J 2017, Schematic Invariants by Reduction to Ground Invariants. julkaisussa Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17). Proceedings of the AAAI Conference on Artificial Intelligence, AAAI, Sivut 3644-3650, AAAI Conference on Artificial Intelligence, San Francisco, California, Yhdysvallat, 04/02/2017. <https://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14955>

Schematic Invariants by Reduction to Ground Invariants. / Rintanen, Jussi.

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17). AAAI, 2017. s. 3644-3650 (Proceedings of the AAAI Conference on Artificial Intelligence).

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference contribution › Scientific › vertaisarvioitu

TY - GEN

T1 - Schematic Invariants by Reduction to Ground Invariants

AU - Rintanen, Jussi

N1 - Conference code: 31

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

M3 - Conference contribution

T3 - Proceedings of the AAAI Conference on Artificial Intelligence

SP - 3644

EP - 3650

BT - Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)

PB - AAAI

T2 - AAAI Conference on Artificial Intelligence

Y2 - 4 February 2017 through 9 February 2017

ER -

Schematic Invariants by Reduction to Ground Invariants

Abstrakti

Julkaisusarja

Conference

Pääsy asiakirjaan

OpenUrl-saatavuus

Sormenjälki

Projektit

Suomalainen laskennallisen päättelyn huippuyksikkö

Laitteet

Science-IT

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