Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World
Book
Urquhart, N. (2022)
Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World. Cham: Springer. https://doi.org/10.1007/978-3-030-98108-2
This book explains classic routing and transportation problems and solutions, before offering insights based on successful real-world solutions. The chapters in Part I introdu...
Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches
Journal Article
Alissa, M., Sim, K., & Hart, E. (in press)
Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches. Journal of Heuristics, https://doi.org/10.1007/s10732-022-09505-4
We propose a novel technique for algorithm-selection, applicable to optimisation domains in which there is implicit sequential information encapsulated in the data, e.g., in o...
Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers
Conference Proceeding
Cardoso, R. P., Hart, E., Burth Kurka, D., & Pitt, J. (2022)
Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers. In Applications of Evolutionary Computation: EvoApplications 2022 (418-434). https://doi.org/10.1007/978-3-031-02462-7_27
Using Neuroevolution combined with Novelty Search to promote behavioural diversity is capable of constructing high-performing ensembles for classification. However, using grad...
Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn
Book Chapter
Hart, E. (2022)
Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn. In A. E. Smith (Ed.), Women in Computational Intelligence: Key Advances and Perspectives on Emerging Topics (187-203). Cham: Springer. https://doi.org/10.1007/978-3-030-79092-9_9
Standard approaches to developing optimisation algorithms tend to involve selecting an algorithm and tuning it to work well on a large set of problem instances from the domain...
A Novel Nomad Migration-Inspired Algorithm for Global Optimization
Journal Article
Lin, N., Fu, L., Zhao, L., Hawbani, A., Tan, Z., Al-Dubai, A., & Min, G. (2022)
A Novel Nomad Migration-Inspired Algorithm for Global Optimization. Computers and Electrical Engineering, 100, Article 107862. https://doi.org/10.1016/j.compeleceng.2022.107862
Nature-inspired computing (NIC) has been widely studied for many optimization scenarios. However, miscellaneous solution space of real-world problem causes it is challenging t...
Morpho-evolution with learning using a controller archive as an inheritance mechanism
Journal Article
Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., De Carlo, M., …Tyrrell, A. M. (in press)
Morpho-evolution with learning using a controller archive as an inheritance mechanism. IEEE Transactions on Cognitive and Developmental Systems, https://doi.org/10.1109/tcds.2022.3148543
Most work in evolutionary robotics centres on evolving a controller for a fixed body-plan. However, previous studiessuggest that simultaneously evolving both controller ...
Deep Learning in Mobile Computing: Architecture, Applications, and Future Challenges
Journal Article
Yang, X., Tan, Z., & Luo, Z. (2021)
Deep Learning in Mobile Computing: Architecture, Applications, and Future Challenges. Mobile Information Systems, 2021, 1-3. https://doi.org/10.1155/2021/9874724
No abstract available.
Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection
Journal Article
Cui, C., Lu, L., Tan, Z., & Hussain, A. (2021)
Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection. Neurocomputing, 464, 252-264. https://doi.org/10.1016/j.neucom.2021.08.026
Segmentation-based methods are widely used for scene text detection due to their superiority in describing arbitrary-shaped text instances. However, two major problems still e...
A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics
Book Chapter
Stone, C., Hart, E., & Paechter, B. (2021)
A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics. In N. Pillay, & R. Qu (Eds.), Automated Design of Machine Learning and Search Algorithms (91-107). Springer. https://doi.org/10.1007/978-3-030-72069-8_6
Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, usually rely on a set of domain-specific low-level heuristics which exist below the doma...
A novel tensor-information bottleneck method for multi-input single-output applications
Journal Article
Lu, L., Ren, X., Cui, C., Tan, Z., Wu, Y., & Qin, Z. (2021)
A novel tensor-information bottleneck method for multi-input single-output applications. Computer Networks, 193, https://doi.org/10.1016/j.comnet.2021.108088
Ensuring timeliness and mobility for multimedia computing is a crucial task for wireless communication. Previous algorithms that utilize information channels, such as the info...