2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms
Lapok, P., Lawson, A., & Paechter, B. (2018)
2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms. In H. Rodrigues, J. Herskovits, C. Mota Soares, A. Araújo, J. Guedes, J. Folgado, …J. Madeira (Eds.), EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization, 926-937. doi:10.1007/978-3-319-97773-7_80
In this paper, we investigate the ability of genetic representation methods to describe two-dimensional outline shapes, in order to use them in a generative design system. A s...
Use of machine learning techniques to model wind damage to forests
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019)
Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022
This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at r...
Athos - A Model Driven Approach to Describe and Solve Optimisation Problems
Hoffman, B., Chalmers, K., Urquhart, N., & Guckert, M. (2019)
Athos - A Model Driven Approach to Describe and Solve Optimisation Problems. https://doi.org/10.1145/3300111.3300114
Implementing solutions for optimisation problems with general purpose high-level programming languages is a time consuming task that can only be carried out by professional so...
Simulating the actions of commuters using a multi-agent system
Urquhart, N., Powers, S., Wall, Z., Fonzone, A., Ge, J., & Polhill, G. (2019)
Simulating the actions of commuters using a multi-agent system. Journal of Artificial Societies and Social Simulation, 22(2), https://doi.org/10.18564/jasss.4007
The activity of commuting to and from a place of work affects not only those travelling but also wider society through their contribution to congestion and pollution. It is de...
From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes
Gkatzia, D., Rieser, V., Bartie, P., & Mackaness, W. (2015)
From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 1936-1942. https://doi.org/10.18653/v1/d15-1224
Predicting the success of referring expressions (RE) is vital for real world applications such as navigation systems. Traditionally, research has focused on studying Referring...
A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation
Gkatzia, D., Cercas Curry, A., Rieser, V., & Lemon, O. (2015)
A Game-Based Setup for Data Collection and Task-Based Evaluation of Uncertain Information Presentation. In Proceedings of the 15th European Workshop on Natural Language Generation, 112-113. https://doi.org/10.18653/v1/w15-4720
Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores, such as probabilities. A concrete example of such data is weather data. We w...
A Snapshot of NLG Evaluation Practices 2005 - 2014
Gkatzia, D., & Mahamood, S. (2015)
A Snapshot of NLG Evaluation Practices 2005 - 2014. https://doi.org/10.18653/v1/w15-4708
In this paper we present a snapshot of endto-end NLG system evaluations as presented in conference and journal papers1 over the last ten years in order to better understand th...
Generating and Evaluating Landmark-Based Navigation Instructions in Virtual Environments
Cercas Curry, A., Gkatzia, D., & Rieser, V. (2015)
Generating and Evaluating Landmark-Based Navigation Instructions in Virtual Environments. In Proceedings of the 15th European Workshop on Natural Language Generation, 90-94. https://doi.org/10.18653/v1/w15-4715
Referring to landmarks has been identified to lead to improved navigation instructions. However, a previous corpus study suggests that human “wizards” also choose to refer to ...
Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data
Gkatzia, D., Hastie, H., & Lemon, O. (2014)
Comparing Multi-label Classification with Reinforcement Learning for Summarisation of Time-series Data. In Proceedings of the Conference Volume 1: Long Papers, 1231-1240. https://doi.org/10.3115/v1/p14-1116
We present a novel approach for automatic report generation from time-series data, in the context of student feedback generation. Our proposed methodology treats content selec...
Simulating Dynamic Vehicle Routing Problems with Athos
Hoffman, B., Guckert, M., Chalmers, K., & Urquhart, N. (2019)
Simulating Dynamic Vehicle Routing Problems with Athos. In Proceedings of the 33rd International ECMS Conference on Modelling and Simulation ECMS 2019, (296-302). https://doi.org/10.7148/2019-0296
Complex routing problems, such as vehicle routing problems with additional constraints, are both hard to solve and hard to express in a form that is accessible to the human ex...