Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Reem Alansary and Nourhan Ehab

Affiliation: Department of Computer Science and Engineering, German University in Cairo, Cairo, Egypt

Keyword(s): Neuro-Symbolic AI, Reinforcement Learning, Representation Learning.

Abstract: The advantages of neurosymbolic systems as solvers of sequential decision problems have captured the attention of reseachers in the field of AI. The combination of perception and cognition allows for constructing learning agents with memory. In this position paper, we argue that the decision-making abilities of such knowledge-augmented solvers transcend those of black-box function approximators alone as the former can generalize through inductive reasoning to behave optimally in unknown states and still remain fully or partially interpretable. We present a novel approach leveraging a knowledge base structured as a layered directed acyclic graph, facilitating reasoned generalization in the absence of complete information.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.134.117.239

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Alansary, R. and Ehab, N. (2024). Towards Knowledge-Augmented Agents for Efficient and Interpretable Learning in Sequential Decision Problems. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4; ISSN 2184-433X, SciTePress, pages 1014-1019. DOI: 10.5220/0012430900003636

@conference{icaart24,
author={Reem Alansary and Nourhan Ehab},
title={Towards Knowledge-Augmented Agents for Efficient and Interpretable Learning in Sequential Decision Problems},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={1014-1019},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012430900003636},
isbn={978-989-758-680-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Towards Knowledge-Augmented Agents for Efficient and Interpretable Learning in Sequential Decision Problems
SN - 978-989-758-680-4
IS - 2184-433X
AU - Alansary, R.
AU - Ehab, N.
PY - 2024
SP - 1014
EP - 1019
DO - 10.5220/0012430900003636
PB - SciTePress