An Ontology-Based Augmented Observation for Decision-Making in Partially Observable Environments

Saeedeh Ghanadbashi, Akram Zarchini, Fatemeh Golpayegani

2023

Abstract

Decision-making is challenging for agents operating in partially observable environments. In such environments, agents’ observation is often based on incomplete, ambiguous, and noisy sensed data, which may lead to perceptual aliasing. This means there might be distinctive states of the environment that appear the same to the agents, and agents fail to take suitable actions. Currently, machine learning, collaboration, and practical reasoning techniques are used to improve agents’ observation and their performance in such environments. However, their long exploration and negotiation periods make them incapable of reacting in real time and making decisions on the fly. The Ontology-based Observation Augmentation Method (OOAM) proposed here, improves agents’ action selection in partially observable environments using domain ontology. OOAM generates an ontology-based schema (i.e., mapping low-level sensor data to high-level concepts), and infers implicit observation data from explicit ones. OOAM is evaluated in a job shop scheduling environment, where the required sensed data to process the orders can be delayed or corrupted. The results show that the average utilization rate and the total processed orders have increased by 17% and 25% respectively compared to Trust Region Policy Optimization (TRPO) as a state-of-the-art method.

Paper Citation

in Harvard Style

Ghanadbashi S., Zarchini A. and Golpayegani F. (2023). An Ontology-Based Augmented Observation for Decision-Making in Partially Observable Environments. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-623-1, pages 343-354. DOI: 10.5220/0011793200003393

in Bibtex Style

@conference{icaart23,
author={Saeedeh Ghanadbashi and Akram Zarchini and Fatemeh Golpayegani},
title={An Ontology-Based Augmented Observation for Decision-Making in Partially Observable Environments},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2023},
pages={343-354},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011793200003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - An Ontology-Based Augmented Observation for Decision-Making in Partially Observable Environments
SN - 978-989-758-623-1
AU - Ghanadbashi S.
AU - Zarchini A.
AU - Golpayegani F.
PY - 2023
SP - 343
EP - 354
DO - 10.5220/0011793200003393