Cost Partitioning for Multi-agent Planning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00336493" target="_blank" >RIV/68407700:21230/19:00336493 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scitepress.org/PublicationsDetail.aspx?ID=cz7omPvUXhA=&t=1" target="_blank" >https://www.scitepress.org/PublicationsDetail.aspx?ID=cz7omPvUXhA=&t=1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0007256600400049" target="_blank" >10.5220/0007256600400049</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cost Partitioning for Multi-agent Planning

Popis výsledku v původním jazyce

Similarly to classical planning, heuristics play a crucial role in Multi-Agent Planning (MAP). Especially, the question of how to compute a distributed heuristic so that the information is shared effectively has been studied widely. This question becomes even more intriguing if we aim to preserve some degree of privacy, or admissibility of the heuristic. The works published so far aimed mostly at providing an ad-hoc distribution protocol for a particular heuristic. In this work, we propose a general framework for distributing heuristic computation based on the technique of cost partitioning. This allows the agents to compute their heuristic values separately and the global heuristic value as an admissible sum. We evaluate the presented techniques in comparison to the baseline of locally computed heuristics and show that the approach based on cost partitioning improves the heuristic quality over the baseline.

Název v anglickém jazyce

Cost Partitioning for Multi-agent Planning

Popis výsledku anglicky

Similarly to classical planning, heuristics play a crucial role in Multi-Agent Planning (MAP). Especially, the question of how to compute a distributed heuristic so that the information is shared effectively has been studied widely. This question becomes even more intriguing if we aim to preserve some degree of privacy, or admissibility of the heuristic. The works published so far aimed mostly at providing an ad-hoc distribution protocol for a particular heuristic. In this work, we propose a general framework for distributing heuristic computation based on the technique of cost partitioning. This allows the agents to compute their heuristic values separately and the global heuristic value as an admissible sum. We evaluate the presented techniques in comparison to the baseline of locally computed heuristics and show that the approach based on cost partitioning improves the heuristic quality over the baseline.

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

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 11th International Conference on Agents and Artificial Intelligence

ISBN

978-989-758-350-6

ISSN

2184-433X

e-ISSN

—

Počet stran výsledku

10

Strana od-do

40-49

Název nakladatele

SCITEPRESS – Science and Technology Publications, Lda

Místo vydání

Lisboa

Místo konání akce

Praha

Datum konání akce

19. 2. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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