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Strengthening Potential Heuristics with Mutexes and Disambiguations

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00341808" target="_blank" >RIV/68407700:21230/20:00341808 - isvavai.cz</a>

  • Result on the web

    <a href="https://aaai.org/ojs/index.php/ICAPS/article/view/6653" target="_blank" >https://aaai.org/ojs/index.php/ICAPS/article/view/6653</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Strengthening Potential Heuristics with Mutexes and Disambiguations

  • Original language description

    Potential heuristics assign a numerical value (potential) to each fact and compute the heuristic value for a given state as the sum of these potentials. A mutex is an invariant stating that a certain combination of facts cannot be part of any reachable state. In this paper, we use mutexes to improve potential heuristics in two ways. First, we show that the mutex-based disambiguations of the goal and preconditions of operators leads to a less constrained linear program yielding stronger heuristics. Second, we utilize mutexes in a construction of new optimization functions based on counting of the number of states containing certain sets of facts. The experimental evaluation shows a significant increase in the number of solved tasks.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • 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

    2020

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling

  • ISBN

    978-1-57735-824-4

  • ISSN

    2334-0835

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    124-133

  • Publisher name

    AAAI Press

  • Place of publication

    Menlo Park

  • Event location

    Nancy

  • Event date

    Oct 26, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article