Outputs (40)

Analysing the predictivity of features to characterise the search space (2022)
Conference Proceeding
Durgut, R., Aydin, M. E., Ihshaish, H., & Rakib, A. (2022). Analysing the predictivity of features to characterise the search space. In E. Pimenidis, P. Angelov, C. Jayne, A. Papaleonidas, & M. Aydin (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings; Part IV (1-13). https://doi.org/10.1007/978-3-031-15937-4_1

Exploring search spaces is one of the most unpredictable challenges that has attracted the interest of researchers for decades. One way to handle unpredictability is to characterise the search spaces and take actions accordingly. A well-characterised... Read More about Analysing the predictivity of features to characterise the search space.

Transfer learning for operator selection: A reinforcement learning approach (2022)
Journal Article
Durgut, R., Aydin, M. E., & Rakib, A. (2022). Transfer learning for operator selection: A reinforcement learning approach. Algorithms, 15(1), Article 24. https://doi.org/10.3390/a15010024

In the past two decades, metaheuristic optimisation algorithms (MOAs) have been increasingly popular, particularly in logistic, science, and engineering problems. The fundamental characteristics of such algorithms are that they are dependent on a par... Read More about Transfer learning for operator selection: A reinforcement learning approach.

Memory-constrained context-aware reasoning (2022)
Conference Proceeding
Uddin, I., Rakib, A., Ali, M., & Vinh, P. C. (2022). Memory-constrained context-aware reasoning. In P. Cong Vinh, & A. Rakib (Eds.), Context-Aware Systems and Applications (133-146). https://doi.org/10.1007/978-3-030-93179-7_11

The context-aware computing paradigm introduces environments, known as smart spaces, which can unobtrusively and proactively assist their users. These systems are currently mostly implemented on mobile platforms considering various techniques, includ... Read More about Memory-constrained context-aware reasoning.

A probabilistic logic for resource-bounded multi-agent systems (2019)
Presentation / Conference
Nguyen, H. N., & Rakib, A. (2019, August). A probabilistic logic for resource-bounded multi-agent systems. Paper presented at 28th International Joint Conference on Artificial Intelligence, Macao, China

Resource-bounded alternating-time temporal logic (RB-ATL), an extension of Coalition Logic (CL) and Alternating-time Temporal Logic (ATL), allows reasoning about resource requirements of coalitions in concurrent systems. However, many real-world syst... Read More about A probabilistic logic for resource-bounded multi-agent systems.

Probabilistic resource-bounded alternating-time temporal logic (2019)
Presentation / Conference
Nguyen, H. N., & Rakib, A. (2019, May). Probabilistic resource-bounded alternating-time temporal logic. Poster presented at International Conference on Autonomous Agents and Multiagent Systems, Montreal, Canada

This paper extends resource-bounded ATL (RB-ATL) with probabilistic reasoning and provides the syntax and semantics of the resulting logic, probabilistic resource-bounded ATL (pRB-ATL).

Model checking ontology-driven reasoning agents using strategy and abstraction (2019)
Journal Article
Rakib, A., & Faruqui, R. U. (2021). Model checking ontology-driven reasoning agents using strategy and abstraction. Concurrency and Computation: Practice and Experience, 33(2), Article e5205. https://doi.org/10.1002/cpe.5205

We present a framework for the modelling, specification and verification of ontology-driven multi-agent rule-based systems (MASs). We assume that each agent executes in a separate process and that they communicate via message passing. The proposed ap... Read More about Model checking ontology-driven reasoning agents using strategy and abstraction.

Smart space system interoperability (2019)
Conference Proceeding
Abdur, R. (2019). Smart space system interoperability. In Proceedings of the 3rd International Workshop on (Meta)Modelling for Healthcare Systems (16-23)

This paper presents our research approach which uses and integrates the terminologies and inference mechanism towards the development of functionally correct systems for smart spaces, considering the recent advances in the area of ontology-based mode... Read More about Smart space system interoperability.

An Efficient Rule-Based Distributed Reasoning Framework for Resource-bounded Systems (2018)
Journal Article
Rakib, A., & Uddin, I. (2019). An Efficient Rule-Based Distributed Reasoning Framework for Resource-bounded Systems. Mobile Networks and Applications, 24(1), 82-99. https://doi.org/10.1007/s11036-018-1140-x

© 2018, The Author(s). Over the last few years, context-aware computing has received a growing amount of attention among the researchers in the IoT and ubiquitous computing community. In principle, context-aware computing transforms a physical enviro... Read More about An Efficient Rule-Based Distributed Reasoning Framework for Resource-bounded Systems.

A resource-aware preference model for context-aware systems (2018)
Journal Article
Uddin, I., & Rakib, A. (2018). A resource-aware preference model for context-aware systems. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 217, 3-13. https://doi.org/10.1007/978-3-319-77818-1_1

© 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. In mobile computing, context-awareness has recently emerged as an effective approach for building adaptive pervasive computing applications. Many of... Read More about A resource-aware preference model for context-aware systems.

Modeling and Reasoning about Preference-Based Context-Aware Agents over Heterogeneous Knowledge Sources (2017)
Journal Article
Uddin, I., Rakib, A., Haque, H. M. U., & Vinh, P. C. (2018). Modeling and Reasoning about Preference-Based Context-Aware Agents over Heterogeneous Knowledge Sources. Mobile Networks and Applications, 23(1), 13-26. https://doi.org/10.1007/s11036-017-0899-5

© 2017, The Author(s). This paper presents a conceptual framework and multi-agent model for context-aware decision support in dynamic smart environments based on heterogeneous knowledge sources. A Protégé plug-in for rules extraction from distributed... Read More about Modeling and Reasoning about Preference-Based Context-Aware Agents over Heterogeneous Knowledge Sources.