All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Privacy-Concerned Multiagent Planning

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F16%3A00234399" target="_blank" >RIV/68407700:21730/16:00234399 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21230/16:00234399

  • Result on the web

    <a href="http://link.springer.com/article/10.1007%2Fs10115-015-0887-7" target="_blank" >http://link.springer.com/article/10.1007%2Fs10115-015-0887-7</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s10115-015-0887-7" target="_blank" >10.1007/s10115-015-0887-7</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Privacy-Concerned Multiagent Planning

  • Original language description

    Coordinated sequential decision making of a team of cooperative agents can be described by principles of multiagent planning. Provided that the mechanics of the environment the agents act in is described as a deterministic transitions system, an appropriate planning model is MA-Strips. Multiagent planning modeled as MA-Strips prescribes exactly what information has to be kept private and which information can be communicated in order to coordinate toward shared or individual goals. We propose a multiagent planning approach which combines compilation for a classical state-of-the-art planner together with a compact representation of local plans in the form of finite-state machines. Proving soundness and completeness of the approach, the planner efficiency is further boosted up using distributed delete-relaxation heuristics and using an approximative local plan analysis. We experimentally evaluate applicability of our approach in full privacy setting where only public information can be communicated. We analyze properties of standard multiagent benchmarks from the perspective of classification of private and public information. We show that our approach can be used with different privacy settings and that it outperforms state-of-the-art planners designed directly for particular privacy classification.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA13-22125S" target="_blank" >GA13-22125S: Deterministic Domain-independent Multi-agent 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

Data specific for result type

  • Name of the periodical

    Knowledge and Information Systems

  • ISSN

    0219-1377

  • e-ISSN

  • Volume of the periodical

    48

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    38

  • Pages from-to

    581-618

  • UT code for WoS article

    000382106300004

  • EID of the result in the Scopus database

    2-s2.0-84944571776