The MADLA planner: Multi-agent Planning by Combination of Distributed and Local Heuristic Search
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00313561" target="_blank" >RIV/68407700:21230/17:00313561 - isvavai.cz</a>
Result on the web
<a href="http://www.sciencedirect.com/science/article/pii/S0004370217301042" target="_blank" >http://www.sciencedirect.com/science/article/pii/S0004370217301042</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.artint.2017.08.007" target="_blank" >10.1016/j.artint.2017.08.007</a>
Alternative languages
Result language
angličtina
Original language name
The MADLA planner: Multi-agent Planning by Combination of Distributed and Local Heuristic Search
Original language description
Real world applications often require cooperation of multiple independent entities. Classical planning is a well established technique solving various challenging problems such as logistic planning, factory process planning, military mission planning and high-level planning for robots. Multi-agent planning aims at solving similar problems in the presence of multiple independent entities (agents). Even though such entities might want to cooperate in order to fulfill a common goal, they may want to keep their internal information and processes private. In such case, we talk about privacy-preserving multi-agent planning.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Artificial Intelligence
ISSN
0004-3702
e-ISSN
1872-7921
Volume of the periodical
252
Issue of the periodical within the volume
November
Country of publishing house
GB - UNITED KINGDOM
Number of pages
36
Pages from-to
175-210
UT code for WoS article
000413377800008
EID of the result in the Scopus database
2-s2.0-85028949695