Thursday, October 30, 2008

Work Update

Readers of the blog might have been wondering why I been interested in Second Life (click here to see blog posts on Second Life), and why I been exploring fine scale modelling of the London housing market and what this has to do with GIS and ABM. As part of the CASA seminar series, I was asked to give a talk about some of my work from the last year. The talk was entitled "Modelling Cities: An Approach using Agent-Based Models and GIS' which pulled together these topics. The abstract or the talk is below:

The Agent-based modelling (ABM) paradigm is becoming an increasingly used technique to study cities. It allows us to grow social structures in artificial worlds specifically how a set of micro-specifications are sufficient to generate the macro-phenomena of interest. Until recently many applications of agent-based models exploring urban phenomena have used a regular partition of space (cells) to represent space. While these models have provided valuable insights into urban phenomena especially as they can capture geographic detail, they miss geometric detail. This area is critical to good applications but is barely touched upon in the literature. Geometry (points, lines and polygons), forms the skeleton of cities from streets and buildings, through to parks, rivers, etc. The ability to represent the urban environment as a series of points, lines, and polygons allows for different size features such as houses and roads to be directly incorporated into the modelling process onto which other physical and social attributes can be added. Additionally the inclusion of geometry allows us to make agent-based models more realistic compared to representing the urban environment as a series of discrete regular cells. This presentation introduces ABM, explore how agent-based models coupled loosely with geographic information systems (GIS) can be created through illustrated examples focusing on residential location. These applications directly consider geometry when building these artificial worlds and running the simulations. Furthermore, these models highlight how the inclusion of geometry impacts on simulation results. Problems and challenges with this approach and ABM in general will be identified. To conclude we will argue the need for fine scale and extensive datasets of the built and socio-economic environments to ground such models, along with the need to communicate and visualise agent-based models. To this extent we introduce our detailed housing and built environment database for London, which will be used as a building block for agent-based models associated with London. We then explore how such models might be communicated and shared with others using advances in technology, specifically Web 2.0 and Second Life.

Some people have asked for the slides of the talk, so I have made them available, they can be downloaded from here (28MB). Accompanying these I have also made a movie of the talk which give a sense of dynamics from such models.



Any thoughts or comments most welcome.

Monday, October 27, 2008

New Paper: Key challenges in agent-based modelling for geo-spatial simulation

Just found out we (Christian Castle, Mike Batty and myself) have a new article inpress within Computers, Environment and Urban Systems, entitled "Key challenges in agent-based modelling for geo-spatial simulation" Below is the abstract.

Agent-based modelling (ABM) is becoming the dominant paradigm in social simulation due primarily to a worldview that suggests that complex systems emerge from the bottom-up, are highly decentralised, and are composed of a multitude of heterogeneous objects called agents. These agents act with some purpose and their interaction, usually through time and space, generates emergent order, often at higher levels than those at which such agents operate. ABM however raises as many challenges as it seeks to resolve. It is the purpose of this paper to catalogue these challenges and to illustrate them using three somewhat different agent-based models applied to city systems. The seven challenges we pose involve: the purpose for which the model is built, the extent to which the model is rooted in independent theory, the extent to which the model can be replicated, the ways the model might be verified, calibrated and validated, the way model dynamics are represented in terms of agent interactions, the extent to which the model is operational, and the way the model can be communicated and shared with others. Once catalogued, we then illustrate these challenges with a pedestrian model for emergency evacuation in central London, a hypothetical model of residential segregation model tuned to London data, and an agent-based residential location model, for Greater London. The ambiguities posed by this new style of modelling are drawn out as conclusions, and the relative arbitrariness of such modelling highlighted.

Anyone wishing to give us feedback on the article is most welcome.

Tuesday, October 07, 2008

Agent-based models in Second Life

Just a quick update on our work with agent-based modelling (ABM) in Second Life. Below are a series of models that we have created in Second Life as proofs of concept and a test for how well Second Life copes with different types of agent-based models. We have created three models which we demonstrate below.

Our first model is chosen Conway’s Game of Life. The movie below details its inner workings:


Game of Life from Andrew Crooks.


The sound track is 'A Lonely Place without You' by New Inception.

Our second model is Schelling’s (1978) Segregation model. Where through mild tastes and preferences to locate with like groups segregation arises. The above models were chosen as they highlight how classical automata styles of models which have inspired a generation of modellers can be created and explored in Second Life.


Schelling's Segregation Model from Andrew Crooks.


Our third model is a prototype pedestrian evacuation model which is more complex than the previous two and highlights at the variety of models that can be potentially created in Second Life. We first started off with agents randomly walking around a room avoiding each other and walls as the movie below demonstrates.


Random Walking from Andrew Crooks.


Then we took the model further were agents exit the building once an alarm is sounded. Within this model we have designed three different room configurations, from a simple square room, a more complex room with internal walls and tables as obstacles, and a multi-floor building were the agents have to walk down the stairs towards the exit (all of which are shown below). From these three scenarios one can explore how room configurations, obstacles and density of surrounding pedestrians impact on pedestrian egress.

Pedestrian Evacuation Model: simple layout from Andrew Crooks .

To further help understand we record the paths the pedestrians walk when exiting the building. The movie below shows the paths travelled of pedestrians exiting the simple room from the movie above.



Pedestrian Evacuation Model: simple layout-trace movie from Andrew Crooks on Vimeo.



Pedestrian Evacuation Model: complex layout from Andrew Crooks.



Pedestrian Evacuation Model: Multi-floor layout from Andrew Crooks.


All the models where written using the Linden Scripting Language (see Rymaszewski et al., 2007) rather than following a loose coupling approach. Further details (including code and model descriptions) and movies of simulations from the models can be found here. If you use Second Life, you can visit our agent street (The SLURL to go there directly is here). In agent street you can experiment with the models and there are also vending machines which allow you to download the model.



Any thoughts or comments or most welcome.