Lumion, Unity, Agents & Objects

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Crowd, transport and urban simulations are at their roots down to 'Agents' or 'Objects' that are assigned a set of rules as to how to moves in relation to both the environment and other agents around them. 3D Studio Max has a built in 'Crowd and Delegate' system which can be used to assign behaviour and therefore create realistic traffic of pedestrian systems in 3D space.

The movie below displays our first tentative steps to explore emergent behaviour via the introduction of simple rules. The movie starts out with a basic 'wander' behaviour where the agents only knowledge is the shape of the surface. Moving on we assign each of our 'cubes' (of which we have become quite fond of...) a level of vision so they can see ahead and therefore avoid each other and objects in their environment.


Crowd and Delegates - Emergent Behaviour from digitalurban on Vimeo.

Thirdly, the agents seek a 'sphere' which could be viewed as a source of food. While being aware of each other and tweaking the way the cubes move a swarm behaviour emerges. Finally, we introduce competing groups with two priorities, firstly to eat and secondly to stay as a group. The majority choose the group over the food but a couple stray off in search of sustenance and lose the other members.

Previous steps in our visualisation of agent based models are based around a simple flocking examples. This model is an attempt to mimic the flocking of birds, while the resulting motion also resembles schools of fish. The flocks that appear in this model are not created or led in any way by special leader rather, each bird is following exactly the same set of rules, from which flocks emerge.

We have exported the model into 3D Max providing the visualisation below, as ever these are early days but the results seem to run well with 300 'birds' over 1000 frames. The birds are rendered as cubes at the moment for proof of concept:




Flocking in NetLogo exported to 3D Max from digitalurban on Vimeo.
Music "Funkmelon Blooz" (Electronica)

The birds follow three rules: "alignment", "separation", and "cohesion". "Alignment" means that a bird tends to turn so that it is moving in the same direction that nearby birds are moving. "Separation" means that a bird will turn to avoid another bird which gets too close. "Cohesion" means that a bird will move towards other nearby birds (unless another bird is too close). When two birds are too close, the "separation" rule overrides the other two, which are deactivated until the minimum separation is achieved.

The three rules affect only the bird's heading. Each bird always moves forward at the same constant speed.

If we were using the built in Crowd and Delegate system a true 3D flocking system would be possible, but it would be pure visualisation, by importing via NetLogo you gain access to the raw data and thus spatial analysis is possible. It is also quick to model and provides the best of both worlds - 3d visualisation and complex modelling.

While 3D Max is of use for crowd and particle simulation when it comes to modelling complex systems an external package is required, such as NetLogo. The movie below details our first steps at CASA (home of digital urban) to export a basic traffic model from NetLogo into 3D Studio Max. The import script was written by our new PhD student, Ateen Patel and opens up a vast array of opportunities to both visualise and model the city.




Music by The Tedd-Z Cookbook, Aerodrome (Funky Shuffle Remix)

NetLogo is a cross-platform multi-agent programmable modeling environment that is widely. It is particularly well suited for modeling complex systems developing over time. Modelers can give instructions to hundreds or thousands of independent "agents" all operating concurrently. This makes it possible to explore the connection between the micro-level behavior of individuals and the macro-level patterns that emerge from the interaction of many individuals.(Nation Master Encyclopedia).

How does this relate to the city? The next part is to put in real geographical data and to get the agents movies and reacting to each other on a spatial network, more on that to come. Perhaps using a particle system as per the movie below:



Particles in the City from digitalurban on Vimeo.
All of these models are going into our exhibition space to allow a step by step guide to the principles of agent based modelling. At the moment we are weighing up two options - Unity and Lumion. Our previous trials in Unity are below:





Unity is great, it is a fully featured game engine, however we are also looking at Lumion. Lumion, aimed more at direct visualization, is remarkably easy to learn, the movie below is the result of our first 20 minutes working with Lumion from first load to final output. It is merely proof of concept, but taking the output from Max and dragging into Lumion is refreshingly simply:




We will have more on Lumion in future posts...

5 Movies on Particles, Agents and Emergent Behaviour

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Crowd, transport and urban simulations are at their roots down to 'Agents' or 'Objects' that are assigned a set of rules as to how to moves in relation to both the environment and other agents around them. 3D Studio Max has a built in 'Crowd and Delegate' system which can be used to assign behaviour and therefore create realistic traffic of pedestrian systems in 3D space.

The movie below displays our first tentative steps to explore emergent behaviour via the introduction of simple rules. The movie starts out with a basic 'wander' behaviour where the agents only knowledge is the shape of the surface. Moving on we assign each of our 'cubes' (of which we have become quite fond of...) a level of vision so they can see ahead and therefore avoid each other and objects in their environment.

Crowd and Delegates - Emergent Behaviour from digitalurban on Vimeo.

Thirdly, the agents seek a 'sphere' which could be viewed as a source of food. While being aware of each other and tweaking the way the cubes move a swarm behaviour emerges. Finally, we introduce competing groups with two priorities, firstly to eat and secondly to stay as a group. The majority choose the group over the food but a couple stray off in search of sustenance and lose the other members.

Previous steps in our visualisation of agent based models are based around a simple flocking examples

This model is an attempt to mimic the flocking of birds, while the resulting motion also resembles schools of fish. The flocks that appear in this model are not created or led in any way by special leader rather, each bird is following exactly the same set of rules, from which flocks emerge.

We have exported the model into 3D Max providing the visualisation below, as ever these are early days but the results seem to run well with 300 'birds' over 1000 frames. The birds are rendered as cubes at the moment for proof of concept:


Flocking in NetLogo exported to 3D Max from digitalurban on Vimeo.
Music "Funkmelon Blooz" (Electronica)

The birds follow three rules: "alignment", "separation", and "cohesion". "Alignment" means that a bird tends to turn so that it is moving in the same direction that nearby birds are moving. "Separation" means that a bird will turn to avoid another bird which gets too close. "Cohesion" means that a bird will move towards other nearby birds (unless another bird is too close). When two birds are too close, the "separation" rule overrides the other two, which are deactivated until the minimum separation is achieved.

The three rules affect only the bird's heading. Each bird always moves forward at the same constant speed.

If we were using the built in Crowd and Delegate system a true 3D flocking system would be possible, but it would be pure visualisation, by importing via NetLogo you gain access to the raw data and thus spatial analysis is possible. It is also quick to model and provides the best of both worlds - 3d visualisation and complex modelling.

While 3D Max is of use for crowd and particle simulation when it comes to modelling complex systems an external package is required, such as NetLogo. The movie below details our first steps at CASA (home of digital urban) to export a basic traffic model from NetLogo into 3D Studio Max. The import script was written by our new PhD student, Ateen Patel and opens up a vast array of opportunities to both visualise and model the city.


Music by The Tedd-Z Cookbook, Aerodrome (Funky Shuffle Remix)

NetLogo is a cross-platform multi-agent programmable modeling environment that is widely. It is particularly well suited for modeling complex systems developing over time. Modelers can give instructions to hundreds or thousands of independent "agents" all operating concurrently. This makes it possible to explore the connection between the micro-level behavior of individuals and the macro-level patterns that emerge from the interaction of many individuals.(Nation Master Encyclopedia).

How does this relate to the city? The next part is to put in real geographical data and to get the agents movies and reacting to each other on a spatial network, more on that to come. Perhaps using a particle system as per the movie below:

Particles in the City from digitalurban on Vimeo.

All of these models are going into our exhibition space previewed below to allow a step by step guide to the principles of agent based modelling.



The virtual exhibition space has been placed on hold due to work pressures on other projects over the last few months but is something we hope to return to soon.

Crowds and Delegates in 3D Max - Agent Based Modelling and Emergent Behaviour

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Crowd, transport and urban simulations are at their roots down to 'Agents' or 'Objects' that are assigned a set of rules as to how to moves in relation to both the environment and other agents around them. 3D Studio Max has a built in 'Crowd and Delegate' system which can be used to assign behaviour and therefore create realistic traffic of pedestrian systems in 3D space.

The movie below displays our first tentative steps to explore emergent behaviour via the introduction of simple rules. The movie starts out with a basic 'wander' behaviour where the agents only knowledge is the shape of the surface. Moving on we assign each of our 'cubes' (of which we have become quite fond of...) a level of vision so they can see ahead and therefore avoid each other and objects in their environment.

Crowd and Delegates - Emergent Behaviour from digitalurban on Vimeo.

Thirdly, the agents seek a 'sphere' which could be viewed as a source of food. While being aware of each other and tweaking the way the cubes move a swarm behaviour emerges. Finally, we introduce competing groups with two priorities, firstly to eat and secondly to stay as a group. The majority choose the group over the food but a couple stray off in search of sustenance and lose the other members.

All of these models are going into our exhibition space previewed below to allow a step by step guide to the principles of agent based modelling.



The virtual exhibition space should be online for Windows and Mac in the next few weeks.

Second Life: Agent Based Models Update

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As part of joint work with gisagents.blogspot.com we have just finished another part of Agent-Street where agents and avatars can interact with each other. The idea here is to merge iconic and symbolic urban models in a multi-user real time environment:

Agent-Based Modelling in Second Life from Andrew Crooks on Vimeo.

The movie below details Agent-Street and how one can download the models we have created by clicking on the model vending machines. Such vending machines are common features in Second Life and allow users to store objects and scripts in their personal inventory for later use such as rebuilding the models on their own Land or in free sand-boxes. We have been using the Mauve Land for this (SLURL).

In our previous models avatars could only visualise and initiate the models. For example, in the pedestrian evacuation model users could only observe how agents exited the building (in a similar way to professionally developed 3D pedestrian modelling software packages such as STEPS - more on STEPS in a future post.). In this new model, we extend the basic pedestrian evacuation model, so that agents not only consider their environments but also other avatars. In this sense we are not only incorporating iconic and symbolic modelling styles but also adding a further human dimension, moving towards an augmented reality (i.e. as if the agents and the humans were in the same crowd). The movie below details how pedestrian paths change when avoiding an avatar, note how an avatar stationed near the exit impacts on pedestrian egress as agents have to move around it.

We have also set up a website outlining the work in detail (click here) or alternatively if you have a Second Life account this SLurl will take you to the Land, once you teleport to the area, follow the red arrow (beam of red light) into the sky to find Agent-Street. If the models are running slow let us know as we having problems with fish entering our land from a neighbouring island.

Thanks as ever go to NATURE for allowing us use of Second Nature Island to set up the experiments.

CASA Free Two Day Workshop: London 8/9 Jan 09

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For the next couple of days we are away from the blog at the CASA (home of digital urban) two day workshop. Running over the 8th and 9th January 2009 in London: the first day of the event is designed to showcase CASA's use of new technologies for mapping and visualizing information about cities. The second day entails technical workshops, designed primarily for members of the S4 European Spatial Analysis network, but all are welcome, the focus of the second day is agent based modelling. We will be talking through the latest 3D techniques as recently featured on the blog...

We have over 150 people attending but if you are in town then feel free to pop along and we'll try to fit you in..

Click here to see the full program and details about registration .

Flocking: NetLogo to 3DMax

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The next step in our visualisation of agent based models is a simple flocking example.

This model is an attempt to mimic the flocking of birds, while the resulting motion also resembles schools of fish. The flocks that appear in this model are not created or led in any way by special leader rather, each bird is following exactly the same set of rules, from which flocks emerge.

We have exported the model into 3D Max providing the visualisation below, as ever these are early days but the results seem to run well with 300 'birds' over 1000 frames. The birds are rendered as cubes at the moment for proof of concept:


Flocking in NetLogo exported to 3D Max from digitalurban on Vimeo.

Music "Funkmelon Blooz" (Electronica)

The birds follow three rules: "alignment", "separation", and "cohesion". "Alignment" means that a bird tends to turn so that it is moving in the same direction that nearby birds are moving. "Separation" means that a bird will turn to avoid another bird which gets too close. "Cohesion" means that a bird will move towards other nearby birds (unless another bird is too close). When two birds are too close, the "separation" rule overrides the other two, which are deactivated until the minimum separation is achieved.

The three rules affect only the bird's heading. Each bird always moves forward at the same constant speed.

If we were using the built in Crowd and Delegate system a true 3D flocking system would be possible, but it would be pure visualisation, by importing via NetLogo you gain access to the raw data and thus spatial analysis is possible. It is also quick to model and provides the best of both worlds - 3d visualisation and complex modelling.

How does this relate to the city? The next part is to put in real geographical data and to get the agents movies and reacting to each other on a spatial network, more on that to come.

You can download NetLogo from here, its comes with a excellent tutorial so you can start building your own model.

NetLogo to 3DMax: Complex Models and 3D Visualisation

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We have been running a series of posts recently looking at crowd simulation, dynamics and particles in 3D Max. The aim is to visualise the complex systems that make up the city within an environment that allows both clear and easy visualisation and export capabilities to other packages such as Crysis or Google Earth.

While 3D Max is of use for crowd and particle simulation when it comes to modelling complex systems an external package is required, such as NetLogo. The movie below details our first steps at CASA (home of digital urban) to export a basic traffic model from NetLogo into 3D Studio Max. The import script was written by our new PhD student, Ateen Patel and opens up a vast array of opportunities to both visualise and model the city.


NetLogo to 3D Max - Proof of Concept from digitalurban on Vimeo.

Music by The Tedd-Z Cookbook, Aerodrome (Funky Shuffle Remix)

NetLogo is a cross-platform multi-agent programmable modeling environment that is widely. It is particularly well suited for modeling complex systems developing over time. Modelers can give instructions to hundreds or thousands of independent "agents" all operating concurrently. This makes it possible to explore the connection between the micro-level behavior of individuals and the macro-level patterns that emerge from the interaction of many individuals.(Nation Master Encyclopedia)

We will have more posts on complex systems and visualising the city over the coming weeks and months.

See http://gisagents.blogspot.com/ for more on modelling, agents and the city.

Particles in the City: Agents For Understanding Flow and City Dynamics

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We thought we would put up a quick post on 'what we are currently doing'... At the moment we are looking into simulating and visualising flow in the city, linked into our earlier 3D based agent work. Its early days but using a particle system linked to known wind dynamics and a 3D city model you can create a rapid visualisation of the dispersion of particles. This maybe useful if, for example, a 'dirty bomb' was exploded or if some sort of contamination was detected.



Taking this further it can also be used for crowd modelling and pedestrian evacuation analysis within the cityscape. We are using our 'fantasy city' as a first test bed, rather than our London model at the moment as its easier to work with in the first stage of development...

You can see how we created the model via our Fantasy City Tutorial for 3D Studio Max.

Cellular Automaton and Agents in Second Life: Game of Life, Segregation and Evacuation Simulation

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The Game of Life is a cellular automaton devised by the British mathematician John Horton Conway in 1970. It is perhaps the best-known example of a cellular automaton and as such formed the perfect starting point for looking at running models in Second Life.

The Game of Life sits alongside Schelling's Segregation Model and a Pedestrian Evacuation Model developed as part of a series of agent based models for our paper entitled 'Agent Street: Agent Based Modelling in Second Life'. The paper is currently about to be submitted for peer review/publication and should be available, subject to acceptance, late 2008.

The movie below details our Game of Life model running in Second Life:


Game of Life from Andrew Crooks on Vimeo.

Sound track'A Lonely Place without You' by New Inception.

The universe of the Game of Life is an infinite two-dimensional orthogonal grid of square cells, each of which is in one of two possible states, live or dead. Every cell interacts with its eight neighbours, which are the cells that are directly horizontally, vertically, or diagonally adjacent. At each step in time, the following transitions occur:

1. Any live cell with fewer than two live neighbours dies, as if by loneliness.
2. Any live cell with more than three live neighbours dies, as if by overcrowding.
3. Any live cell with two or three live neighbours lives, unchanged, to the next generation.
4. Any dead cell with exactly three live neighbours comes to life.

The initial pattern constitutes the 'seed' of the system. The first generation is created by applying the above rules simultaneously to every cell in the seed — births and deaths happen simultaneously, and the discrete moment at which this happens is sometimes called a tick. (In other words, each generation is a pure function of the one before.) The rules continue to be applied repeatedly to create further generations (ref Wikipedia)

Moving up a level of sophistication is Schelling's Segregation Model. Schelling originally demonstrated the concept with coins on a chess board. Using Second Life we have transferred the ideas utilising coloured spheres inside a grid of houses, as the movie below illustrates:


Schelling's Segregation Model from Andrew Crooks on Vimeo.

Schelling demonstrated how through mild tastes and preferences to locate in areas with similar people, large scale patterns of segregation could arise.

Finally we have developed in Second Life a pedestrian evacuation model. This is a much more accurate simulation of real life than the previous two models (the Game of Life and Segregation Model) and the rules that govern the agents are notably more complicated.


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

The clip above shows how agents exit a building once an alarm is sounded. Within the model, a model second is not the same as a real second so we have edited the clip so every model second is one real second just to give a sense of dynamics within the model.

Take a look at gisagents.blogspot.com for more thoughts on agent based modelling within both 2D and 3D environments, written by Andrew Crooks of CASA. Crooks is lead author of the forthcoming paper, his blog is the first place to look for a more in depth analysis of agent based modelling.

These are perhaps early steps but the ability to integrate human controlled avatars into models of building/environment evacuation, via environments such as Second Life, presents an intriguing step forward. Indeed, one that has the potential to lead to a more comprehensive understanding of evacuation behavior and ultimately of course better architectural design.

Game of Life and Agents in Second Life

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Agent-Based Modelling in Second Life from Andrew Crooks on Vimeo.

First off apologies for the distinct lack of posts - a thing called 'work' got in the way this week with various deadlines and conference presentations. We have given ourselves a suitable talking to for missing blog posts and now we are back...

First up is the movie above, which explains some of our downtime. At CASA we are using Second Life as a online urban laboratory to explore issues pertaining to urban planning and public debate in a visually 3D collaborative environment.

We have created three agent-based models ranging from Conways Game of Life, Schelling's segregation model and a pedestrian evacuation model. The models are proofs of concept to demonstrate how experts, model builders and the non specialist can view, interact and discuss agent-based models within Second Life.

The music was not our choice :) take a look at gisagents.blogspot.com for the full story and more of a background on agents in Second Life.

Real-Time Motion Planning for Crowds in Cities

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Real-time crowd simulation requires fast, realistic methods for path planning as well as obstacle avoidance. The movie below details from EPFL Virtual Reality Lab, Switzerland's Motion Planning Approach:



Navigation Graphs allow efficient navigation planning and simulation for crowds. They can be automatically computed from the mesh of the environment where the crowd is to be set. In real-time, EPFL's solution is able to simulate and render tens of thousands of people.

Take a look at EPFL's website for more information, papers and movies.

Posts: 4th International Conference on e-Social Science

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We are currently in Manchester for the 4th International Conference on e-Social Science, running for three days the conference covers a number of subjects relevant to the blog.
I'm presenting a paper entitled 'Agent-Based Geospatial Simulation: Techniques, Tools and Advances in Three-Dimensional Visualisation', for those interested the abstract is below.

The use of agent-based modeling for geospatial simulation has traditionally been a two-dimensional activity with the third dimension rarely ventured into. In many ways this is due to the nature of the discipline and a focus on theory rather than outreach and end of game visualization. The world of video entertainment has made significant advances in artificial intelligence over the recent years, combined with the rise of graphic card technologies these developing ‘sandbox’ environments provide a new opportunity for agent-based modeling.

Standard three-dimensional modeling packages such as 3D Studio Max offer a level of built in agent-based modeling capabilities through ‘crowd and delegate’ logic systems. While these are limited to some extent, it is possible to take x/y/z output from standard geospatial agent-based modeling approaches and import them into visual software. This approach allows loose coupling between model and visualisation systems allowing a more realistic view of any given models output.

We explore the use of 3D Studio Max and gaming technologies, such as Crysis, though a series of examples before concluding with a look at using collaborative virtual environments such as Second Life to both visualise and run agent-based geospatial models.

3D Agent Based Modelling in Second Life

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Second Life is a natural home to agent based modelling, while not as graphically impressive as high end solutions such as 3D Studio Max, it does allow real-time data analysis and tracking.

The movie below shows our first tentative steps in CASA to setting up a agent based model in the Second Life environment:



Our next step is to look at examples such as evacuation analysis and pedestiran movement in the cityscape, the movie below issustrates our earlier example in 3D Studio Max - we should be able to port this into Second Life:



If you would like to know more about agent based modelling take a look at http://gisagents.blogspot.com/

Agents in the City: Vision

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Our last weeks series of posts on 3D Agent Based Models using 3D Max has been interesting (at least we have found it interesting). It is easy to set up any number of agents to swarm or wander within a set radius but adding behaviours beyond swarming is more difficult.

It seem to be down to 'vision' and how far the agents can 'see' ahead of them. In 3D Studio Max agents seem to only be capable of a complete 360x180 degree field of view or avoidance, this creates either large areas of exclusion or areas where agents fail to 'see' objects coming.

Our latest movie below illustrates this, the agents are now in our city model from the Greeble a City Tutorial:



At the moment the agents tend to get run over by the bus and roam inside the buildings, despite being set to avoid, still it is work in progress...

gisagents.blogspot.com have an interesting post on Pacman: is it an agent-based model? for those interested - a 3D Pacman would actually be quite easy as its a simple 'Seek' behaviour interlinked with paths.

Simulating Traffic in 3D Cities: Agents, Shockwaves and Grids

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Simulating traffic is a science in itself with each car acting as an agent that is aware of its surroundings. It is notoriously difficult to create convincing traffic flow in 3D packages without input from specialist simulations and as such its a good challenge for our recent explorations of using agents in 3D Max to populate city models.

New Scientist highlighted the 'Shockwave' theory of traffic simulation this month with an article on how a team of Japanese researchers has recreated the phenomenon on a test-track for the first time.

The mathematical theory behind these so-called "shockwave" jams was developed more than 15 years ago using models that show jams appear from nowhere on roads carrying their maximum capacity of free-flowing traffic – typically triggered by a single driver slowing down.



With simple agents in 3D Max our first movie interestingly produces similar results:



If you then set up 'three teams' linked to a network with behaviour based on varying speed and avoidance calculations you can create a basic traffic flow simulation.



As we have said, these are first steps and there are some obvious issues to iron out with the aim to import the traffic flow into scenes such as our 'Greeble City Tutorial' model illustrated below:

Interestingly the work going on just to our left using the Crysis game engine for traffic flow is proceeding at a notable rate, we should have a movie of this tomorrow...

Read more about the Shockwave Theory and NetLogo.

Towards Modelling Behaviour in 3D Cities: 3D Agents for Architecture

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The second in what is looking like a series of posts on 3D Agent Based Modelling in cities - in short on placing crowd, pedestrian and transport behavior into 3D models.

Yesterday's post covered our first steps, developing 'Ant Like' behaviors on a surface, our next movie displays a degree of intelligence in our agents:



The agents are now aware of the environment around them and each other, as such they avoid collisions while wandering around the surface. As we mentioned this is 'first step' work and we are aware that there are advanced crowd simulations out there. We are taking a slightly different approach and as ever with the blog we will write a tutorial on the system soon as its more advanced.


It would be interesting to hear any thoughts on this line of posts and if you would like to know more about agents take a look at http://gisagents.blogspot.com/

Agents in the City: First Steps to Crowd Based Architectual Modelling

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Yesterday we posted about roads in 3d models and how small details begin to bring the 3d city to life. The same goes for pedestrians and modes of transport, in essence these objects populate the city and add a significant level of realism.

Crowd and transport simulation is at its roots down to 'Agents' or 'Objects' that are assigned a set of rules as to how to moves in relation to both the environment and other agents around them. 3D Studio Max has a built in 'Crowd and Delegate' system which can be used to assign behavior and therefore create realistic traffic of pedestrian systems in 3D space.

Our movie below displays our first tentative steps using the system to create an 'Ant Like' behavior on a surface:



Ok its far from a crowd in a city but the principle is there. We don't often put up 'early development' movies but this should be an interesting learning curve for anyone wanting to populate a 3D City. At the same time as using 3D Max we are also using Crysis for realtime agent based modelling, more on that a little later...

If you would like to know more about Agents take a look at http://gisagents.blogspot.com/ - a blog written a mere two desks away from where we are currently sat...

Agents from NetLogo to 3D Studio Max

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Those nice people over at GISAgents sent us an extremely interesting paper entitled 'Enactment Software: Spatial Designs using Agents-Based Models. Written by T. Narahara of Harvard University, Cambridge, MA it explores the integration of Netlogo with 3D Studio Max.

Narahara states that In the field of architectural design profession, it is fairly typical for designers to build 3-d models of their own building designs within the CAD (computer aided design) software environments such as AutoCAD, 3d Studio MAX. The proposed method introduces walking scale figures in geometric models.

The goal is to add a sense of place to the geometry, and augment the representation of its spatial quality for designers and audience. Through agent-based computation using NetLogo, they move inside the model and display various behaviors in reaction to spatial characteristics such as transparent surface, opaque surface, perforation and furniture.

The full paper, available as a .pdf, is well worth a read for anyone interested in 3DMax or agent based modelling in general.

Update - See NetLogo to 3D Max, Code and Example Movies.

See http://www.gisagents.blogspot.com for more details on agents in general.

Second Life - Simulation and Agents in a Box

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If you look under the hood of Second Life there is more to the virtual environment than a first look around the 'Help' island provides. Using the Second Life Scripting Language - an internal, event-driven, C/Java-style language which allows you to control object and avatar behavior - it is possible to build any number of simulations from agent based models to modular architectural components.

In terms of agents Teconic has created a simulation of ants locating food, and leaving a pheromone trail for other ants to follow. The movie below details the simulation and provides an interesting insight into the possibilities for agent based modelling in Second Life:



In terms of city creation and architecture the scripting language is increasingly being used to create modular 'out of the box' solutions. The latest of which is designed to allow users to set up a small urban centre in under 30 minutes using 'Sim in a Box' a system which allows over 4 million possible outcomes due to its modular nature.

The movie below details the simulation:



We will be taking a close look at the Second Life Scripting Language for both agent based modeling and architectural components over the coming weeks.

Understanding GIS and Agent Based Modelling

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Understanding Agent Based Modelling and GIS is easier to say than do. What do you do when you have to decide the suitability of a pedestrian evacuation software application to assess the evacuation process of a building? The answer is to turn to our fellow blog at CASA - that of GIS and Agent Based Modelling.

They have a series of working papers online as well as a number of powerpoint presentations. If you wanted to know everything about Agents but were afraid to ask, GIS and Agent Based Modelling is a good place to start...