Endomorphisms of Classical Planning Tasks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00350200" target="_blank" >RIV/68407700:21230/21:00350200 - isvavai.cz</a>

Výsledek na webu

<a href="https://ojs.aaai.org/index.php/AAAI/article/view/17406" target="_blank" >https://ojs.aaai.org/index.php/AAAI/article/view/17406</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Endomorphisms of Classical Planning Tasks

Popis výsledku v původním jazyce

Detection of redundant operators that can be safely removed from the planning task is an essential technique allowing to greatly improve performance of planners. In this paper, we employ structure-preserving maps on labelled transition systems (LTSs), namely endomorphisms well known from model theory, in order to detect redundancy. Computing endomorphisms of an LTS induced by a planning task is typically infeasible, so we show how to compute some of them on concise representations of planning tasks such as finite domain representations and factored LTSs. We formulate the computation of endomorphisms as a constraint satisfaction problem (CSP) that can be solved by an off-the-shelf CSP solver. Finally, we experimentally verify that the proposed method can find a sizeable number of redundant operators on the standard benchmark set.

Název v anglickém jazyce

Endomorphisms of Classical Planning Tasks

Popis výsledku anglicky

Detection of redundant operators that can be safely removed from the planning task is an essential technique allowing to greatly improve performance of planners. In this paper, we employ structure-preserving maps on labelled transition systems (LTSs), namely endomorphisms well known from model theory, in order to detect redundancy. Computing endomorphisms of an LTS induced by a planning task is typically infeasible, so we show how to compute some of them on concise representations of planning tasks such as finite domain representations and factored LTSs. We formulate the computation of endomorphisms as a constraint satisfaction problem (CSP) that can be solved by an off-the-shelf CSP solver. Finally, we experimentally verify that the proposed method can find a sizeable number of redundant operators on the standard benchmark set.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GJ18-24965Y" target="_blank" >GJ18-24965Y: Multi-agentní plánování s ochranou soukromých informací</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence

ISBN

978-1-57735-866-4

ISSN

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e-ISSN

2374-3468

Počet stran výsledku

9

Strana od-do

11835-11843

Název nakladatele

Association for the Advancement of Artificial Intelligence (AAAI)

Místo vydání

Palo Alto, California

Místo konání akce

Virtual Conference

Datum konání akce

2. 2. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000681269803058