Nick Malleson's lectures for the 2014 Lipari School on Computational Social Science on Modeling Spatio-Temporal Reasoning in Complex Social Systems.
July 20 - July 26, 2014, Lipari Island, Italy
Developments in Smart Cities are underpinned by a big data "revolution". New data from sources such as public transport systems, mobile telephones, social media, etc., are unparalleled in their scope, scale and resolution, and can reveal deep insight into the complex micro-interactions that drive urban systems. These new insights are being used effectively to improve the efficiency, sustainability and resilience of cities. However, in order to reap the greatest benefit from these new data, Smart Cities require reliable models to estimate the impacts of new initiatives or to highlight unfavourable emerging trends that require intervention. Agent-based modelling is a methodology that simulates behaviour at the level of the individual unit (e.g. person, household, business) and is therefore ideally suited for modelling complex urban phenomena. However, the benefits of modelling individuals are often tempered by difficulties in accounting for complexities in simulating human behaviour. This workshop will introduce the technique of Agent-Based Modelling in relation to advances in Smart Cities and the Big Data "revolution". In particular, it will explore the ways in which human behaviour can be simulated in computer models. The use of Agent-Based Modelling, coupled with new social insights from Big Data, is a fundamental element to a successful Smart City agenda.
The lecture slides are produced using HTML. They are available here.
There is also a pdf printout of the slides, available here.
The lecture slides are produced using HTML. They are available here.
There is also a pdf printout of the slides, available here.