The Relationship of Dynamic Entropy Maximising and Agent-Based Approaches in Urban Modelling
- Joel DeardenAffiliated withCentre for Applied Spatial Analysis (CASA), University College Email author
- , Alan WilsonAffiliated withCentre for Applied Spatial Analysis (CASA), University College
Entropy maximising models are well established within the field of urban modelling as a method for predicting flows of people or material within an urban system. The dynamic urban retail model (Harris and Wilson, Environ Plan A 10:371–388, 1978) is one of the most well known applications of this technique and is an example of a BLV (Boltzmann-Lotka-Volterra) model. We define an agent-based model (ABM) of urban retail and explore whether it can be made equivalent to a BLV model. Application of both models to the metropolitan county of South Yorkshire in the UK indicates that both models produce similar outputs. This direct comparison provides some insights into the differences and similarities of each approach, as well as highlighting the relative strengths and weaknesses. The ABM has the potential to be easier to disaggregate, while the entropy maximising model is more computationally efficient.
- The Relationship of Dynamic Entropy Maximising and Agent-Based Approaches in Urban Modelling
- Book Title
- Agent-Based Models of Geographical Systems
- pp 705-720
- Print ISBN
- Online ISBN
- Springer Netherlands
- Copyright Holder
- Springer Science+Business Media B.V.
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- Editor Affiliations
- ID1. School of Geography, University of Leeds
- ID2. , Department of Computational Social Scien, George Mason University
- ID3. International Institute of Applied Syste
- ID4. Ctr. Advanced Spatial Analysis, University College London
- Author Affiliations
- 1. Centre for Applied Spatial Analysis (CASA), University College, London, UK
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