All Outputs (3)

Achieving goals using reward shaping and curriculum learning (2023)
Presentation / Conference
Studley, M., hansen, M., anca, M., thomas, J., & pedamonti, D. (2023, November). Achieving goals using reward shaping and curriculum learning. Paper presented at Future Technologies Conference, San Francisco

Real-time control for robotics is a popular research area in the reinforcement learning community. Through the use of techniques such as reward shaping, researchers have managed to train online agents across a multitude of domains. Despite these adva... Read More about Achieving goals using reward shaping and curriculum learning.

Embedding citizens within airborne microplastic and microfibre research (2023)
Journal Article
Williams, B., De Vito, L., Margarida Sardo, A., Pringle, K., Hansen, M., Taylor, M., …Hayes, E. (2023). Embedding citizens within airborne microplastic and microfibre research. Cambridge Prisms: Plastics, 1(e11), 1-5. https://doi.org/10.1017/plc.2023.11

Microplastics are ubiquitous in our environment but their presence in air is less well understood. Homes are likely a key source of airborne microplastics and microfibres to the environment owing to the frequent use and storage of plastics and textil... Read More about Embedding citizens within airborne microplastic and microfibre research.

Transformers and human-robot interaction for delirium detection (2023)
Conference Proceeding
Jeffcock, J., Hansen, M., & Ruiz Garate, V. (2023). Transformers and human-robot interaction for delirium detection. In 2023 ACM/IEEE International Conference on Human-Robot Interaction (466-474). https://doi.org/10.1145/3568162.3576971

An estimated 20% of patients admitted to hospital wards are affected by delirium. Early detection is recommended to treat underlying causes of delirium, however workforce strain in general wards often causes it to remain undetected. This work propose... Read More about Transformers and human-robot interaction for delirium detection.