Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution
Conference Proceeding
Marrero, A., Segredo, E., León, C., & Hart, E. (in press)
Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution. In Genetic and Evolutionary Computation Conference (GECCO ’24), July 14–18, 2024, Melbourne, VIC, Australia. https://doi.org/10.1145/3638529.3654028
The ability to generate example instances from a domain is important in order to benchmark algorithms and to generate data that covers an instance-space in order to train mach...
A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control
Conference Proceeding
Montague, K., Hart, E., & Paechter, B. (2024)
A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control. In S. Smith, J. Correia, & C. Cintrano (Eds.), Applications of Evolutionary Computation: 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings, Part I (178-193). https://doi.org/10.1007/978-3-031-56852-7_12
Behaviour trees (BTs) are commonly used as controllers in robotic swarms due their modular composition and to the fact that they can be easily interpreted by humans. From an a...
On the Utility of Probing Trajectories for Algorithm-Selection
Conference Proceeding
Renau, Q., & Hart, E. (2024)
On the Utility of Probing Trajectories for Algorithm-Selection. In Applications of Evolutionary Computation. EvoApplications 2024 (98-114). https://doi.org/10.1007/978-3-031-56852-7_7
Machine-learning approaches to algorithm-selection typically take data describing an instance as input. Input data can take the form of features derived from the instance desc...
Utilizing the Ensemble Learning and XAI for Performance Improvements in IoT Network Attack Detection
Conference Proceeding
Kalutharage, C. S., Liu, X., Chrysoulas, C., & Bamgboye, O. (2024)
Utilizing the Ensemble Learning and XAI for Performance Improvements in IoT Network Attack Detection. In Computer Security. ESORICS 2023 International Workshops (125-139). https://doi.org/10.1007/978-3-031-54129-2_8
How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction
Conference Proceeding
Orme, M., Yu, Y., & Tan, Z. (in press)
How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction.
This paper concerns the pressing need to understand and manage inappropriate language within the evolving human-robot interaction (HRI) landscape. As intelligent systems and r...
Image Forgery Detection using Cryptography and Deep Learning
Conference Proceeding
Oke, A., & Babaagba, K. O. (2024)
Image Forgery Detection using Cryptography and Deep Learning. In Big Data Technologies and Applications. BDTA 2023 (62-78). https://doi.org/10.1007/978-3-031-52265-9_5
The advancement of technology has undoubtedly exposed everyone to a remarkable array of visual imagery. Nowadays, digital technology is eating away the trust and historical co...
DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences
Conference Proceeding
Koniaris, B., Sinclair, D., & Mitchell, K. (in press)
DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences.
DanceMark is an open telemetry framework designed for latency-sensitive real-time networked immersive experiences, focusing on online dancing in virtual reality within the Dan...
Evolving Behavior Allocations in Robot Swarms
Conference Proceeding
Hallauer, S., Nitschke, G., & Hart, E. (2024)
Evolving Behavior Allocations in Robot Swarms. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (1526-1531). https://doi.org/10.1109/SSCI52147.2023.10371934
Behavioral diversity is known to benefit problem-solving in biological social systems such as insect colonies and human societies, as well as in artificial distributed systems...
enunlg: a Python library for reproducible neural data-to-text experimentation
Conference Proceeding
Howcroft, D. M., & Gkatzia, D. (2023)
enunlg: a Python library for reproducible neural data-to-text experimentation. In Proceedings of the 16th International Natural Language Generation Conference: System Demonstrations (4-5
Over the past decade, a variety of neural ar-chitectures for data-to-text generation (NLG) have been proposed. However, each system typically has its own approach to pre-and p...
Building a dual dataset of text-and image-grounded conversations and summarisation in Gàidhlig (Scottish Gaelic)
Conference Proceeding
Howcroft, D. M., Lamb, W., Groundwater, A., & Gkatzia, D. (2023)
Building a dual dataset of text-and image-grounded conversations and summarisation in Gàidhlig (Scottish Gaelic). In Proceedings of the 16th International Natural Language Generation Conference (443-448
Gàidhlig (Scottish Gaelic; gd) is spoken by about 57k people in Scotland, but remains an under-resourced language with respect to natural language processing in general and na...