Skip to main content

Research Repository

Advanced Search

A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms (2023)
Conference Proceeding
Montague, K., Hart, E., Paechter, B., & Nitschke, G. (in press). A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms. In EVOStar 2023

Designing controllers for a swarm of robots such that collabo-rative behaviour emerges at the swarm level is known to be challenging. Evolutionary approaches have proved promising, with attention turning more recently to evolving repertoires of dive... Read More about A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms.

Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches (2023)
Journal Article
Alissa, M., Sim, K., & Hart, E. (2023). Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches. Journal of Heuristics, 29(1), 1-38. 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 online bin-packing. Specifically we train two types of recurrent neural netw... Read More about Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches.

Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World (2022)
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 introduce and explain the traveling salesperson problem (TSP), vehicle routing pro... Read More about Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World.

A Compact Wideband Circularly Polarized Planar Monopole Antenna with Axial Ratio Bandwidth Entirely Encompassing the Antenna Bandwidth (2022)
Journal Article
Mousa, F. M., Al-Yasir, Y. I. A., Ali, N. T., Gharbia, I., See, C. H., & Abd-Alhameed, R. (2022). A Compact Wideband Circularly Polarized Planar Monopole Antenna with Axial Ratio Bandwidth Entirely Encompassing the Antenna Bandwidth. IEEE Access, 10, 81828-81835. https://doi.org/10.1109/ACCESS.2022.3196610

The antenna presented in this study is a compact wideband monopole with wideband circular polarization that can be used across the whole antenna bandwidth. A rectangular C-shaped patch is partially covered by a ground plane in the proposed planar mon... Read More about A Compact Wideband Circularly Polarized Planar Monopole Antenna with Axial Ratio Bandwidth Entirely Encompassing the Antenna Bandwidth.

Machine Learning Enabled Quantitative Ultrasound Techniques for Tissue Differentiation (2022)
Journal Article
Thomson, H., Yang, S., & Cochran, S. (2022). Machine Learning Enabled Quantitative Ultrasound Techniques for Tissue Differentiation. Journal of Medical Ultrasonics, 49, 517-528. https://doi.org/10.1007/s10396-022-01230-6

Quantitative ultrasound (QUS) infers properties about tissue microstructure from backscattered via radio-frequency ultrasound data. This paper describes how to implement the most practical QUS parameters using an ultrasound research system for tissue... Read More about Machine Learning Enabled Quantitative Ultrasound Techniques for Tissue Differentiation.

Single-Element and MIMO Circularly Polarized Microstrip Antennas with Negligible Back Radiation for 5G Mid-Band Handsets (2022)
Journal Article
Alnahwi, F. M., Al-Yasir, Y. I. A., See, C. H., & Abd-Alhameed, R. A. (2022). Single-Element and MIMO Circularly Polarized Microstrip Antennas with Negligible Back Radiation for 5G Mid-Band Handsets. Sensors, 22(8), Article 3067. https://doi.org/10.3390/s22083067

In this paper, single-element and MIMO microstrip antenna with two pairs of unequal slits is proposed as a circularly polarized antenna with negligible back radiation for 5G mid-band handsets. The unequal pairs of slits are engraved on the antenna pa... Read More about Single-Element and MIMO Circularly Polarized Microstrip Antennas with Negligible Back Radiation for 5G Mid-Band Handsets.

Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers (2022)
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 gradient descent to train evolved architectures during the search can be comput... Read More about Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers.

Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn (2022)
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 of interest. Once deployed, the algorithm remains static, failing to impro... Read More about Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn.

A Novel Nomad Migration-Inspired Algorithm for Global Optimization (2022)
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 to guarantee the global optimum. Besides, cumbersome structure and complex p... Read More about A Novel Nomad Migration-Inspired Algorithm for Global Optimization.

Morpho-evolution with learning using a controller archive as an inheritance mechanism (2022)
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 and body-plan could open up many interesting possibilities. However... Read More about Morpho-evolution with learning using a controller archive as an inheritance mechanism.

Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection (2021)
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 exist: (1) current label generation techniques are mostly empirical and lack... Read More about Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection.

A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics (2021)
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 domain-barrier and are manipulated by the hyper-heuristic itself. However, for... Read More about A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics.

On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme (2021)
Conference Proceeding
Goff, L. K. L., & Hart, E. (2021). On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme. In GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion (1498-1502). https://doi.org/10.1145/3449726.3463156

We investigate a hierarchical scheme for the joint optimisation of robot bodies and controllers in a complex morphological space. An evolutionary algorithm optimises body-plans while a separate learning algorithm is applied to each body generated to... Read More about On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme.

Reward-Reinforced Generative Adversarial Networks for Multi-agent Systems (2021)
Journal Article
Zheng, C., Yang, S., Parra-Ullauri, J., Garcia-Dominguez, A., & Bencomo, N. (2022). Reward-Reinforced Generative Adversarial Networks for Multi-agent Systems. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(3), 479 - 488. https://doi.org/10.1109/TETCI.2021.3082204

Multi-agent systems deliver highly resilient and adaptable solutions for common problems in telecommunications, aerospace, and industrial robotics. However, achieving an optimal global goal remains a persistent obstacle for collaborative multi-agent... Read More about Reward-Reinforced Generative Adversarial Networks for Multi-agent Systems.

A novel tensor-information bottleneck method for multi-input single-output applications (2021)
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, Article 108088. 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 information bottleneck method, have shown great performance and efficiency, whi... Read More about A novel tensor-information bottleneck method for multi-input single-output applications.

WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets (2021)
Conference Proceeding
Pitt, J., Burth Kurka, D., Hart, E., & Cardoso, R. P. (2021). WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets. In Applications of Evolutionary Computation: EvoApplications 2021 Proceedings (649-664). https://doi.org/10.1007/978-3-030-72699-7_41

In order to address scalability issues, which can be a challenge for Deep Learning methods, we propose Wide Learning of Diverse Architectures-a model that scales horizontally rather than vertically, enabling distributed learning. We propose a distrib... Read More about WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets.

Vehicular Computation Offloading for Industrial Mobile Edge Computing (2021)
Journal Article
Zhao, L., Yang, K., Tan, Z., Song, H., Al-Dubai, A., & Zomaya, A. (2021). Vehicular Computation Offloading for Industrial Mobile Edge Computing. IEEE Transactions on Industrial Informatics, 17(11), 7871-7881. https://doi.org/10.1109/TII.2021.3059640

Due to the limited local computation resource, industrial vehicular computation requires offloading the computation tasks with time-delay sensitive and complex demands to other intelligent devices (IDs) once the data is sensed and collected collabora... Read More about Vehicular Computation Offloading for Industrial Mobile Edge Computing.

Evolution of Diverse, Manufacturable Robot Body Plans (2020)
Conference Proceeding
Buchanan, E., Le Goff, L., Hart, E., Eiben, A. E., De Carlo, M., Li, W., …Tyrrell, A. M. (2020). Evolution of Diverse, Manufacturable Robot Body Plans. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI) (2132-2139). https://doi.org/10.1109/SSCI47803.2020.9308434

Advances in rapid prototyping have opened up new avenues of research within Evolutionary Robotics in which not only controllers but also the body plans (morphologies) of robots can evolve in real-time and real-space. However, this also introduces new... Read More about Evolution of Diverse, Manufacturable Robot Body Plans.

Improved Adaptive Impedance Matching for RF Front-End Systems of Wireless Transceivers (2020)
Journal Article
Alibakhshikenari, M., Virdee, B. S., Shukla, . P., See, C. H., Abd-Alhameed, R., Falcone, F., & Limiti, . E. (2020). Improved Adaptive Impedance Matching for RF Front-End Systems of Wireless Transceivers. Scientific Reports, 10(1), Article 14065 (2020). https://doi.org/10.1038/s41598-020-71056-0

In this paper an automatic adaptive antenna impedance tuning algorithm is presented that is based on quantum inspired genetic optimization technique. The proposed automatic quantum genetic algorithm (AQGA) is used to find the optimum solution for a l... Read More about Improved Adaptive Impedance Matching for RF Front-End Systems of Wireless Transceivers.