The Bartlett Centre for Advanced Spatial Analysis


Planning as Conflict Resolution - Michael Batty

16 October 2019, 5:00 pm–6:00 pm

Event Information

Open to





A Maclachlan


85: 26 Bedford Way
26 Bedford Way
United Kingdom

For many years, physical planning has been articulated as a process of resolving conflict between different opinions about what constitutes the best locations for various facilities, activities, and land uses.  These conflicts are generic to social action and the definition of a plan which resolves such conflicts has been the quest of planners, designers and policy makers ever since physical planning became institutionalised in the late 19th century.

Here we define the process as one where key actors or stakeholders hold different values with respect to the best locations and suggest how such conflicts can be resolved through methods for pooling their different opinions about these best locations exist. A consensus is achieved if the various actors are able to communicate their opinions to one another, either directly or indirectly through an appropriate social network and from these emerge the relative importance that the different actors' opinions play in the final consensus.

In short, the methods we will demonstrate are able to generate the relative importance of each actor in the process, hence the relative importance of each opinion in the final mix. These methods map onto many different formal systems ranging from Markov Averaging to Artificial Neural Nets but here we focus on developing a variant which enables us to take simple maps which represent the relative importance of each location with respect the opinion of each actor, generate a network by comparing or ‘correlating’ the maps, and thence resolving the conflicts through an averaging procedure. We concluded by speculating on how such models can be tuned to real processes for all we are currently able to do in the absence of detailed observations of how conflicts are actually resolved, is to illustrate the methods for hypothetical processes but in real situations.

We demonstrate all this for a semi-real ‘toy’ problem of land development in the heart of London where a small set of stakeholder agents have different degrees of interest and control in and over a small set of land and building sites (parcels).

About the Speaker

Professor Michael Batty

at Centre for Advanced Spatial Analysis

Michael Batty is Bartlett Professor of Planning at University College London where he is Chair of the Centre for Advanced Spatial Analysis (CASA). He has worked on computer models of cities and their visualisation since the 1970s and has published several books, such as Cities and Complexity (MIT Press, 2005) and The New Science of Cities (MIT Press, 2013). Both books won the Alonso Prize of the North American Regional Science Association.

His most recent book Inventing Future Cities was published by MIT Press in late 2018.  His blogs www.complexcity.info cover the science underpinning the technology of cities and his posts and lectures on big data and smart cities are at www.spatialcomplexity.info. Prior to his current position, he was Professor of City Planning and Dean of the School of Environmental Design at the University of Wales at Cardiff from 1979 to 1990 and then Director of the National Center for Geographic Information and Analysis at the State University of New York at Buffalo from 1990 to 1995.

He is a Fellow of the British Academy (FBA) and the Royal Society (FRS), was awarded the CBE in the Queen’s Birthday Honours in 2004 and the 2013 recipient of the Lauréat Prix International de Géographie Vautrin Lud. In 2015 he received the Gold Medal of the Royal Geographical Society for his work on the science of cities. In 2016, he received the Senior Scholar Award of the Complex Systems Society and the Gold Medal of the Royal Town Planning Institute. In 2018, he was awarded the Waldo Tobler prize for GI Science of the Austrian Academy of Sciences and in 2019, he was elected as a Fellow of the Regional Science Association. 

Other events in this series