Computing Multi-Agent Heuristics Additively
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00307286" target="_blank" >RIV/68407700:21230/16:00307286 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Computing Multi-Agent Heuristics Additively
Original language description
Similarly to classical planning, heuristics play a crucial role in most multi-agent and privacy-preserving multi-agent planning systems. It has been shown that distributed heuristics may crucially improve the search guidance, but are costly in terms of communication and computation time and are often a source of privacy concerns. One solution is to compute a heuristic additively, in the sense that each agent can compute its part of the heuristic independently and obtain a complete heuristic estimate by summing up the individual parts. In this preliminary paper, we propose a technique based on cost-partitioning allowing us to use any heuristic in such a way.
Czech name
—
Czech description
—
Classification
Type
O - Miscellaneous
CEP classification
JC - Computer hardware and software
OECD FORD branch
—
Result continuities
Project
<a href="/en/project/GJ15-20433Y" target="_blank" >GJ15-20433Y: Heuristic Search for Multiagent and Factored Planning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů