Adaptive Knowledge Representation with KERAIA: A Naval Warfare Case Study

Stephen Richard Varey; Alessandro Di Stefano; The Anh Han

doi:10.1109/skima66621.2025.11155477

Adaptive Knowledge Representation with KERAIA: A Naval Warfare Case Study

Stephen Richard Varey
, Alessandro Di Stefano
, The Anh Han

Teesside University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper introduces KERAIA, a novel framework for symbolic knowledge engineering designed to address the challenges of representing, reasoning with, and executing knowledge in dynamic and complex environments. KERAIA extends Minsky's frame-based reasoning model to incorporate Clouds of Knowledge, Dynamic Relations (DRels), and Lines of Thought (LoTs) and Cloud Elaboration. These constructs enable adaptive knowledge inheritance, contextual reasoning, and dynamic updates while maintaining high expressiveness and inference efficiency. KERAIA adheres to explainable AI principles, supporting traceability and interpretability in decision-making. A case study in naval warfare highlights KERAIA's versatility and real-world applicability.

Original language	English
Title of host publication	Proceedings - 2025 16th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2025
Editors	Keshav Dahal, Zeeshan Pervez, Marco Gilardi
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665457347
ISBN (Print)	9781665457347
DOIs	https://doi.org/10.1109/skima66621.2025.11155477
Publication status	Published - 16 Sept 2025
Event	16th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2025 - Paisley, United Kingdom Duration: 9 Jun 2025 → 11 Jun 2025

Conference

Conference	16th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2025
Country/Territory	United Kingdom
City	Paisley
Period	9/06/25 → 11/06/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Access to Document

10.1109/skima66621.2025.11155477

Cite this

Varey, S. R., Di Stefano, A., & Han, T. A. (2025). Adaptive Knowledge Representation with KERAIA: A Naval Warfare Case Study. In K. Dahal, Z. Pervez, & M. Gilardi (Eds.), Proceedings - 2025 16th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2025 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/skima66621.2025.11155477

Varey, Stephen Richard ; Di Stefano, Alessandro ; Han, The Anh. / Adaptive Knowledge Representation with KERAIA : A Naval Warfare Case Study. Proceedings - 2025 16th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2025. editor / Keshav Dahal ; Zeeshan Pervez ; Marco Gilardi. Institute of Electrical and Electronics Engineers Inc., 2025.

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title = "Adaptive Knowledge Representation with KERAIA: A Naval Warfare Case Study",

abstract = "This paper introduces KERAIA, a novel framework for symbolic knowledge engineering designed to address the challenges of representing, reasoning with, and executing knowledge in dynamic and complex environments. KERAIA extends Minsky's frame-based reasoning model to incorporate Clouds of Knowledge, Dynamic Relations (DRels), and Lines of Thought (LoTs) and Cloud Elaboration. These constructs enable adaptive knowledge inheritance, contextual reasoning, and dynamic updates while maintaining high expressiveness and inference efficiency. KERAIA adheres to explainable AI principles, supporting traceability and interpretability in decision-making. A case study in naval warfare highlights KERAIA's versatility and real-world applicability.",

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Varey, SR, Di Stefano, A & Han, TA 2025, Adaptive Knowledge Representation with KERAIA: A Naval Warfare Case Study. in K Dahal, Z Pervez & M Gilardi (eds), Proceedings - 2025 16th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2025. Institute of Electrical and Electronics Engineers Inc., 16th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2025, Paisley, United Kingdom, 9/06/25. https://doi.org/10.1109/skima66621.2025.11155477

Adaptive Knowledge Representation with KERAIA: A Naval Warfare Case Study. / Varey, Stephen Richard; Di Stefano, Alessandro ; Han, The Anh.
Proceedings - 2025 16th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2025. ed. / Keshav Dahal; Zeeshan Pervez; Marco Gilardi. Institute of Electrical and Electronics Engineers Inc., 2025.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Adaptive Knowledge Representation with KERAIA

T2 - 16th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2025

AU - Varey, Stephen Richard

AU - Di Stefano, Alessandro

AU - Han, The Anh

PY - 2025/9/16

Y1 - 2025/9/16

N2 - This paper introduces KERAIA, a novel framework for symbolic knowledge engineering designed to address the challenges of representing, reasoning with, and executing knowledge in dynamic and complex environments. KERAIA extends Minsky's frame-based reasoning model to incorporate Clouds of Knowledge, Dynamic Relations (DRels), and Lines of Thought (LoTs) and Cloud Elaboration. These constructs enable adaptive knowledge inheritance, contextual reasoning, and dynamic updates while maintaining high expressiveness and inference efficiency. KERAIA adheres to explainable AI principles, supporting traceability and interpretability in decision-making. A case study in naval warfare highlights KERAIA's versatility and real-world applicability.

AB - This paper introduces KERAIA, a novel framework for symbolic knowledge engineering designed to address the challenges of representing, reasoning with, and executing knowledge in dynamic and complex environments. KERAIA extends Minsky's frame-based reasoning model to incorporate Clouds of Knowledge, Dynamic Relations (DRels), and Lines of Thought (LoTs) and Cloud Elaboration. These constructs enable adaptive knowledge inheritance, contextual reasoning, and dynamic updates while maintaining high expressiveness and inference efficiency. KERAIA adheres to explainable AI principles, supporting traceability and interpretability in decision-making. A case study in naval warfare highlights KERAIA's versatility and real-world applicability.

UR - https://www.scopus.com/pages/publications/105017755231

U2 - 10.1109/skima66621.2025.11155477

DO - 10.1109/skima66621.2025.11155477

M3 - Conference contribution

AN - SCOPUS:105017755231

SN - 9781665457347

BT - Proceedings - 2025 16th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2025

A2 - Dahal, Keshav

A2 - Pervez, Zeeshan

A2 - Gilardi, Marco

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 9 June 2025 through 11 June 2025

ER -

Varey SR, Di Stefano A , Han TA. Adaptive Knowledge Representation with KERAIA: A Naval Warfare Case Study. In Dahal K, Pervez Z, Gilardi M, editors, Proceedings - 2025 16th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2025. Institute of Electrical and Electronics Engineers Inc. 2025 doi: 10.1109/skima66621.2025.11155477

Adaptive Knowledge Representation with KERAIA: A Naval Warfare Case Study

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