Analysis of Learning Heuristic Estimates for Grid Planning with Cellular Simultaneous Recurrent Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00372647" target="_blank" >RIV/68407700:21230/23:00372647 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1007/s42979-023-02174-5" target="_blank" >https://doi.org/10.1007/s42979-023-02174-5</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s42979-023-02174-5" target="_blank" >10.1007/s42979-023-02174-5</a>

Result language

angličtina

Original language name

Analysis of Learning Heuristic Estimates for Grid Planning with Cellular Simultaneous Recurrent Networks

Original language description

Automated planning provides a powerful general problem solving tool, however, its need for a model creates a bottleneck that can be an obstacle to using automated planning algorithms in real-world settings. In this work, we propose to use cellular simultaneous recurrent networks (CSRN), to process a planning problem and provide a heuristic value estimate that can more efficiently steer the automated planning algorithms to a solution. Using this particular architecture provides us with a scale-free solution that can be used on any problem domain represented by a planar grid. We train the CSRN architecture on two benchmark domains and provide an analysis of its generalizing and scaling abilities. We also integrate the trained network into a planner and compare its performance against commonly used heuristic functions.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

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)

Publication year

2023

Confidentiality

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

Name of the periodical

SN Computer Science

ISSN

2662-995X

e-ISSN

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Volume of the periodical

4

Issue of the periodical within the volume

6

Country of publishing house

SG - SINGAPORE

Number of pages

22

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85173116731