36 citations · 98 across the 5 of their papers we have counts for
5 papers
Agent-Based Modelling for Urban Analytics: State of the Art and Challenges
Nick Malleson, Mark Birkin, Daniel Birks +5
Agent-based modelling (ABM) is a facet of wider Multi-Agent Systems (MAS) research that explores the collective behaviour of individual `agents', and the implications that their be…
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data
Oscar Giles, Kasra Hosseini, Grigorios Mingas +13
Synthetic datasets are often presented as a silver-bullet solution to the problem of privacy-preserving data publishing. However, for many applications, synthetic data has been sho…
Learning Complex Spatial Behaviours in ABM: An Experimental Observational Study
Sedar Olmez, Dan Birks, Alison Heppenstall
Capturing and simulating intelligent adaptive behaviours within spatially explicit individual-based models remains an ongoing challenge for researchers. While an ever-increasing ab…
Simulating Crowds in Real Time with Agent-Based Modelling and a Particle Filter
Nick Malleson, Kevin Minors, Le-Minh Kieu +3
Agent-based modelling is a valuable approach for systems whose behaviour is driven by the interactions between distinct entities. They have shown particular promise as a means of m…
Dealing with uncertainty in agent-based models for short-term predictions
Le-Minh Kieu, Nicolas Malleson, Alison Heppenstall
Agent-based models (ABM) are gaining traction as one of the most powerful modelling tools within the social sciences. They are particularly suited to simulating complex systems. De…