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Semantically Layered Representation for Planning Problems and Its Usage for Heuristic Computation Using Cellular Simultaneous Recurrent Neural Networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00364355" target="_blank" >RIV/68407700:21230/23:00364355 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.5220/0011691000003393" target="_blank" >https://doi.org/10.5220/0011691000003393</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.5220/0011691000003393" target="_blank" >10.5220/0011691000003393</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Semantically Layered Representation for Planning Problems and Its Usage for Heuristic Computation Using Cellular Simultaneous Recurrent Neural Networks

  • Original language description

    Learning heuristic functions for classical planning algorithms has been a great challenge in the past years. The biggest bottleneck of this technique is the choice of an appropriate description of the planning problem suitable for machine learning. Various approaches were recently suggested in the literature, namely grid-based, image-like, and graph-based. In this work, we extend the latest grid-based representation with layered architecture capturing the semantics of the related planning problem. Such an approach can be used as a domain-independent model for further heuristic learning. This representation keeps the advantages of the grid-structured input and provides further semantics about the problem we can learn from. Together with the representation, we also propose a new network architecture based on the Cellular Simultaneous Recurrent Networks (CSRN) that is capable of learning from such data and can be used instead of a heuristic function in the state-space search algorithms.

  • 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

    2023

  • 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 15th International Conference on Agents and Artificial Intelligence

  • ISBN

    978-989-758-623-1

  • ISSN

    2184-3589

  • e-ISSN

    2184-433X

  • Number of pages

    8

  • Pages from-to

    493-500

  • Publisher name

    SCITEPRESS – Science and Technology Publications, Lda

  • Place of publication

    Lisboa

  • Event location

    Lisbon

  • Event date

    Feb 22, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article