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
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Czech description
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Classification
Type
D - Article in proceedings
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)
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
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