A Policy-Based Blackboard Control Mechanism for Dynamic Prioritization in Multilayered Problems

Hana Munira Muhd Mukhtar; Husna Sarirah Husin; Azizah Rahmat

doi:10.48084/etasr.12826

Authors

Hana Munira Muhd Mukhtar Malaysian Institute of Information Technology, Universiti Kuala Lumpur, Kuala Lumpur, Malaysia
Husna Sarirah Husin School of Computer Science, Taylor's University, Subang Jaya, Malaysia
Azizah Rahmat Malaysian Institute of Information Technology, Universiti Kuala Lumpur, Kuala Lumpur, Malaysia

Volume: 16 | Issue: 2 | Pages: 33202-33210 | April 2026 | https://doi.org/10.48084/etasr.12826

Received: 19 June 2025 | Revised: 25 July 2025 | Accepted: 11 August 2025 | Online: 9 February 2026

Corresponding author: Husna Sarirah Husin

Abstract

This research introduces a new blackboard control mechanism designed to address the weaknesses of conventional systems in managing complex, multilayered problem domains. Existing approaches are constrained by rigid, sequential control structures and limited scalability, making them unsuitable for environments that require adaptive and flexible decision-making. The proposed mechanism provides a standardized coordination framework capable of prioritizing several primary problems along with their associated subproblems. As a proof of concept, the control mechanism is applied to the domain of sustainable timber harvesting, a field characterized by interdependent tasks such as inventory assessment, growth prediction, ecological impact mitigation, and strategic tree selection. The mechanism supports dynamic problem prioritization according to a policy-based technique, allowing the system to adapt to progressing problem-solving needs. This study demonstrates the potential of an improved blackboard control mechanism to enhance decision support in complex, real-world domains.

Keywords:

blackboard control mechanism, multilayered complex problem solving, dynamic prioritization, policy-based technique, sustainable timber harvestin

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References

H. M. Mukhtar, Y. Yahya, A. Rahmat, and R. Ismail, "Damage Cost/Value Clustering in Timber Harvesting Decision Making for Sustainable Forest Management," International Journal of Electrical and Computer Engineering Systems, vol. 12, pp. 31–39, Nov. 2021. DOI: https://doi.org/10.32985/ijeces.12.si.4

H. M. M. Mukhtar and R. Ismail, "The Design of Independent-Uniform Knowledge Sources of Blackboard Architecture in Timber Harvesting Decision-Making," in 2024 18th International Conference on Ubiquitous Information Management and Communication, Kuala Lumpur, Malaysia, Jan. 2024, pp. 1–6. DOI: https://doi.org/10.1109/IMCOM60618.2024.10418421

S. T. Goonatilleke and B. Hettige, "Past, Present and Future Trends in Multi-Agent System Technology," Journal Européen des Systèmes Automatisés, vol. 55, no. 6, pp. 723–739, Dec. 2022. DOI: https://doi.org/10.18280/jesa.550604

B. Hayes-Roth, "A Blackboard Architecture for Control," Artificial Intelligence, vol. 26, no. 3, pp. 251–321. DOI: https://doi.org/10.1016/0004-3702(85)90063-3

D. D. Corkill, "Blackboard Systems," AI Expert, vol. 6, no. 9, pp. 40–47, 1991.

R. Hewett and S. Puangpontip, "On Controlling Drones for Disaster Relief," Procedia Computer Science, vol. 207, pp. 3703–3712, 2022. DOI: https://doi.org/10.1016/j.procs.2022.09.430

G. K. H. Pang, "Blackboard Architecture for Intelligent Control," Control Systems, Robotics and Automation: Intelligent Control Systems, vol. 17, pp. 303–316, 2009.

R. Liscano, A. Manz, E. R. Stuck, R. E. Fayek, and J.-Y. Tigli, "Using a Blackboard to Integrate Multiple Activities and Achieve Strategic Reasoning for Mobile-robot Navigation," IEEE Expert, vol. 10, no. 2, pp. 24–36, Apr. 1995. DOI: https://doi.org/10.1109/64.395354

A. M. De Campos and M. J. Monteiro De Macedo, "A Blackboard Architecture for Perception Planning in Autonomous Vehicles," in Proceedings of the 1992 International Conference on Industrial Electronics, Control, Instrumentation, and Automation, San Diego, CA, USA, 1992, pp. 826–831. DOI: https://doi.org/10.1109/IECON.1992.254524

N. M. Sadeh, D. W. Hildum, T. J. Laliberty, J. McA’Nulty, D. Kjenstad, and A. Tseng, "A Blackboard Architecture for Integrating Process Planning and Production Scheduling," Concurrent Engineering, vol. 6, no. 2, pp. 88–100, June 1998. DOI: https://doi.org/10.1177/1063293X9800600201

S. B. Tor, G. A. Britton, and W. Y. Zhang, "A Knowledge-Based Blackboard Framework for Stamping Process Planning in Progressive Die Design," The International Journal of Advanced Manufacturing Technology, vol. 26, no. 7–8, pp. 774–783, Oct. 2005. DOI: https://doi.org/10.1007/s00170-003-2037-8

M.-R. Joanna and I. Bipin, "A Blackboard System for Generating Poetry," Computer Science, vol. 17, no. 2, 2016, Art. no. 265. DOI: https://doi.org/10.7494/csci.2016.17.2.265

J. Straub, "Modeling Attack, Defense and Threat Trees and the Cyber Kill Chain, ATT&CK and STRIDE Frameworks as Blackboard Architecture Networks," in 2020 IEEE International Conference on Smart Cloud, Washington DC, WA, USA, Nov. 2020, pp. 148–153. DOI: https://doi.org/10.1109/SmartCloud49737.2020.00035

J. Rivard and J. Straub, "Extension of the Blackboard Architecture with Common Properties and Generic Rules." arXiv, 2023.

J. Hance, J. Milbrath, N. Ross, and J. Straub, "Distributed Attack Deployment Capability for Modern Automated Penetration Testing," Computers, vol. 11, no. 3, Feb. 2022, Art. no. 33. DOI: https://doi.org/10.3390/computers11030033

J. Straub, "Application of Robotic Exploration Principles to the Challenge of Cybersecurity Penetration Testing," in 2024 IEEE International Conference on Cyber Security and Resilience, London, United Kingdom, Sept. 2024, pp. 255–261. DOI: https://doi.org/10.1109/CSR61664.2024.10679404

P. Karl and B. Hayes-Roth, An Introduction to Blackboard-Style Systems Organization. Stanford, CA, USA: Knowledge Systems Laboratory, Stanford University, 1997.

J. F. Fontanari, "Reputation Blackboard Systems," Cognitive Systems Research, vol. 50, pp. 29–35, Aug. 2018. DOI: https://doi.org/10.1016/j.cogsys.2018.03.008

A. Boaye Belle, T. C. Lethbridge, M. Garzón, and O. O. Adesina, "Design and Implementation of Distributed Expert Systems: On a Control Strategy to Manage the Execution Flow of Rule Activation," Expert Systems with Applications, vol. 96, pp. 129–148, Apr. 2018. DOI: https://doi.org/10.1016/j.eswa.2017.11.033

D. Janjanam, B. Ganesh, and L. Manjunatha, "Design of an Expert System Architecture: An Overview," Journal of Physics: Conference Series, vol. 1767, no. 1, Feb. 2021, Art. no. 012036. DOI: https://doi.org/10.1088/1742-6596/1767/1/012036

N. Krishnan, "Advancing Multi-Agent Systems Through Model Context Protocol: Architecture, Implementation, and Applications." arXiv, 2025.

A. L. Laureano-Cruces, T. Ramírez-González, L. Sánchez-Guerrero, and J. Ramírez-Rodríguez, "Multi-Agent System for Real Time Planning Using Collaborative Agents," International Journal of Intelligence Science, vol. 04, no. 04, pp. 91–103, 2014. DOI: https://doi.org/10.4236/ijis.2014.44011

T. Pulikottil, L. A. Estrada-Jimenez, H. U. Rehman, J. Barata, S. Nikghadam-Hojjati, and L. Zarzycki, "Multi-Agent Based Manufacturing: Current Trends and Challenges," in 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation, Vasteras, Sweden, Sept. 2021, pp. 1–7. DOI: https://doi.org/10.1109/ETFA45728.2021.9613555

N. Benmoussa, M. Fakhouri Amr, S. Ahriz, K. Mansouri, and E. Illoussamen, "Outlining a Model of an Intelligent Decision Support System Based on Multi Agents," Engineering, Technology & Applied Science Research, vol. 8, no. 3, pp. 2937–2942, June 2018. DOI: https://doi.org/10.48084/etasr.1936

F. Al-Shareefi, G. Chu, and A. Lisitsa, "A Multi-Agent Framework for Penetration Testing: Modelling and Analysing Using Abstract State Machines," in 2024 IEEE International Symposium on Parallel and Distributed Processing with Applications, Kaifeng, China, Oct. 2024, pp. 1021–1028. DOI: https://doi.org/10.1109/ISPA63168.2024.00135

W. Jin, H. Du, B. Zhao, X. Tian, B. Shi, and G. Yang, "A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives." SSRN, 2025. DOI: https://doi.org/10.2139/ssrn.5106265

K. Chour et al., "An Agent-based Modeling Framework for the Multi-UAV Rendezvous Recharging Problem," Robotics and Autonomous Systems, vol. 166, Aug. 2023, Art. no. 104442. DOI: https://doi.org/10.1016/j.robot.2023.104442

J. Jamhuri et al., "Selective logging causes the decline of large-sized mammals including those in unlogged patches surrounded by logged and agricultural areas," Biological Conservation, vol. 227, pp. 40–47, Nov. 2018. DOI: https://doi.org/10.1016/j.biocon.2018.09.004

Y. M. Safiah Yusmah, M. J. Barnsley, and H. Rodziah, "Variation Analysis on Buffer Zone, Cutting-limit and Slope Angles in Timber Harvesting Planning," Malaysian Forester, vol. 73, no. 2, pp. 197–211, July 2010.

I. Saiful and A. Latiff, "Canopy Gap Dynamics and Effects of Selective Logging: A Study in a Primary Hill Dipterocarp Forest in Malaysia," Journal of Tropical Forest Science, vol. 31, no. 2, pp. 175–188, May 2019. DOI: https://doi.org/10.26525/jtfs2019.31.2.175188

A. H. Atiqah, P. P. Rhyma, J. Jamhuri, A. W. Zulfa, M. S. Samsinar, and K. Norizah, "Using Google Earth Imagery to Detect Distribution of Forest Cover Change–is the Technique Practical for Malaysian Forests?," Malaysian Forester, vol. 83, no. 1, pp. 1–15, 2020.

M. Azian et al., "Carbon Emission Assessment from Different Logging Activities in Production Forest of Pahang, Malaysia," Journal of Tropical Forest Science, vol. 31, no. 3, pp. 304–311, Aug. 2019. DOI: https://doi.org/10.26525/jtfs2019.31.3.304

M. Demies, H. Samejima, A. K. Sayok, and G. T. Noweg, "Tree Diversity, Forest Structure and Species Composition in a Logged-over Mixed Dipterocarp Forest, Bintulu, Sarawak, Malaysia," Transitions on Science and Technology, vol. 6, pp. 102–110, Apr. 2019.

N. J. Naim Jemali, M. F. Abd Rhani, M. Muhammad, and N. K. S. Abdul Majid, "Forest Growth Analysis of Ulu Sat Forest Reserve," IOP Conference Series: Earth and Environmental Science, vol. 549, no. 1, Aug. 2020, Art. no. 012039. DOI: https://doi.org/10.1088/1755-1315/549/1/012039

R. Pillay, F. Hua, B. A. Loiselle, H. Bernard, and R. J. Fletcher, "Multiple Stages of Tree Seedling Recruitment Are Altered in Tropical Forests Degraded by Selective Logging," Ecology and Evolution, vol. 8, no. 16, pp. 8231–8242, Aug. 2018. DOI: https://doi.org/10.1002/ece3.4352

Y. Yahya and R. Ismail, "Randomized Technique to Determine the New Seedlings for Simulation of Population Dynamic," in Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication 2019, vol. 935, S. Lee, R. Ismail, and H. Choo, Eds. Cham, Switzerland: Springer International Publishing, 2019, pp. 711–722. DOI: https://doi.org/10.1007/978-3-030-19063-7_57

V. Lesser, R. Fennell, L. Erman, and D. Reddy, "Organization of the Hearsay II Speech Understanding System," IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 23, no. 1, pp. 11–24, Feb. 1975. DOI: https://doi.org/10.1109/TASSP.1975.1162648

V. R. Lesser and L. D. Erman, "A Retrospective View of the Hearsay-II Architecture," in Proceedings of the 5th international joint conference on Artificial intelligence, 1977, pp. 790–800.

R. B. Ismail, "The Use of Artificial Intelligence Techniques for Protein Structure Prediction," Ph.D. dissertation, University of Glasgow, Glasgow, United Kingdom, 1989.