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

Michaela Urbanovská, Antonín Komenda

2023

Abstract

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. We show how to model different problem domains using the proposed representation as well as explain the new neural network architecture and compare its performance in the state-space search against existing classical planning heuristics and heuristics provided by the state-of-the-art.

Paper Citation

in Harvard Style

Urbanovská M. and Komenda A. (2023). Semantically Layered Representation for Planning Problems and Its Usage for Heuristic Computation Using Cellular Simultaneous Recurrent Neural Networks. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 493-500. DOI: 10.5220/0011691000003393

in Bibtex Style

@conference{icaart23,
author={Michaela Urbanovská and Antonín Komenda},
title={Semantically Layered Representation for Planning Problems and Its Usage for Heuristic Computation Using Cellular Simultaneous Recurrent Neural Networks},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={493-500},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011691000003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - Semantically Layered Representation for Planning Problems and Its Usage for Heuristic Computation Using Cellular Simultaneous Recurrent Neural Networks
SN - 978-989-758-623-1
AU - Urbanovská M.
AU - Komenda A.
PY - 2023
SP - 493
EP - 500
DO - 10.5220/0011691000003393