Effective Planning in Resource-Competition Problems by Task Decomposition

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00363597" target="_blank" >RIV/68407700:21230/22:00363597 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/22:00363597

Výsledek na webu

<a href="https://doi.org/10.1609/socs.v15i1.21751" target="_blank" >https://doi.org/10.1609/socs.v15i1.21751</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1609/socs.v15i1.21751" target="_blank" >10.1609/socs.v15i1.21751</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Effective Planning in Resource-Competition Problems by Task Decomposition

Popis výsledku v původním jazyce

Effective planning while competing for limited resources is crucial in many real-world applications such as on-demand transport companies competing for passengers. Planning techniques therefore have to take into account possible actions of an adversarial agent. Such a challenge that can be tackled by leveraging game-theoretical methods such as Double Oracle. This paper aims at the scalability issues arising from combining planning techniques with Double Oracle. In particular, we propose an abstraction-based heuristic for deciding how resources will be collected (e.g. which car goes for which passenger and in which order) and we propose a method for decomposing planning tasks into smaller ones (e.g. generate plans for each car separately). Our empirical evaluation shows that our proposed approach considerably improves scalability compared to the state-of-the-art techniques.

Název v anglickém jazyce

Effective Planning in Resource-Competition Problems by Task Decomposition

Popis výsledku anglicky

Effective planning while competing for limited resources is crucial in many real-world applications such as on-demand transport companies competing for passengers. Planning techniques therefore have to take into account possible actions of an adversarial agent. Such a challenge that can be tackled by leveraging game-theoretical methods such as Double Oracle. This paper aims at the scalability issues arising from combining planning techniques with Double Oracle. In particular, we propose an abstraction-based heuristic for deciding how resources will be collected (e.g. which car goes for which passenger and in which order) and we propose a method for decomposing planning tasks into smaller ones (e.g. generate plans for each car separately). Our empirical evaluation shows that our proposed approach considerably improves scalability compared to the state-of-the-art techniques.

Druh

D - Stať ve sborníku

CEP obor

—

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/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Výzkumné centrum informatiky</a><br>

Návaznosti

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

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the Fifteenth International Symposium on Combinatorial Search

ISBN

978-1-57735-873-2

ISSN

—

e-ISSN

—

Počet stran výsledku

9

Strana od-do

47-55

Název nakladatele

Association for the Advancement of Artificial Intelligence (AAAI)

Místo vydání

Palo Alto, California

Místo konání akce

Vídeň

Datum konání akce

21. 7. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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