New ABM papers on data assimilation and emulation

Counts of pedestrians at different sensors.

We have recently published two new papers from the DUST project. The first, by Dan Tang, introduces a new method that allows ABMs to be sampled using efficient Markov chain sampling. The second, by Minh Kieu, explores the possibilities of emulating ABMs using machine learning.

  • Tang, D. and N. Malleson (2022). Data assimilation with agent-based models using Markov chain sampling. Open Research Europe 2(70). DOI: 10.12688/openreseurope.14800.1 (open access)

  • Kieu, M., H. Nguyen, J.A. Ward and N. Malleson (2022). Towards real-time predictions using emulators of agent-based models. Journal of Simulation 1–18. DOI: 10.1080/17477778.2022.2080008.