WK4: Final Submission - Poster / Text

Swarm Theory, refers to the collective behaviour of decentralised, self-organising agents, and as a result their collective behaviour. A behaviour which, through various internal and external variables defines an overall geometrical form. Variables which internally regard the proportional and relative position and velocity between agents, the state of cluster density within the swarm, and the position of agents with regards to the defined central mass and external boundary. While the overall state of the swarm may be defined by the average velocity of the agents with reference to a particular point, and the swarms interaction with additional swarms, resulting in the swarm adapting the variables of influence experienced by the individual agents.

Utilising these variables as factors of consideration within my project in a conceptual manner, I produced a simulation which allows the responder to define an overall geometrical form based upon the physical movement of individual agents, or points. The external parameters of the swarm is defined through the average individually controlled velocity of clusters within the swarm, while the overall direction and focus is determined by the average position of points in the form of a perlin graph.

The internal mechanism of the swarm however is adjusted through individual clusters, centrally based upon the perlin graphs position in space. Where each agent’s velocity and relative position is definable against the central axis of the perlin graph. Furthermore the individual density scale of each agent is adjustable, allowing collectively with the other variables the scale of the swarm to be adjusted while exploring the influence of relative velocities, position and density.

The iterations which have been presented portray a selection of four separate swarms, which explore the altering of the various variables against one another within a three stage time frame. Through such, the responder is able to grasp the influence of such variables against each agent and their reaction within the swarm.

WK4: Final Submission - Grasshopper File

File: https://docs.google.com/open?id=0B_J5qxu5SupGMlpLa3d6b1BRZDZLTkRHeGo3MTZnQQ

The image and file attached to this post are my final grasshopper files used to produce my swarm theory simulation. The system is broken down into four main components. Firstly the ‘swarm direction’ where a perlin graph is generated as a continuous curve, which the user is able to control the size and shape of. The next section is the ‘core points formation and attachment’ where randomly generated points are attached via a pull mechanism at different strengths to curves of numerous offset iterations. Following this is the ‘secondary point formation and attachment’ where more points are randomly placed and attached to offset curves, however this time curves which have been rotated. Finally is the ‘physics engine’ which controls the movement of all the points, stimulating cluster growth and applying spheres to contextualise the points.

WK4: Final Submission - Renders

The collection of iterations above presents my final renders, carried out on my swarm theory study. Each iteration is explained through the following documentation, moving from swarm one, position one in the upper left corner to swarm four, position three in the low right corner.

SwarmOne.PositionOne: Low central state density with limited movement results in minimal agent dispersion about the central perlin axis, as individual behaviour of agents remains stable.

SwarmOne.PositionTwo: Central velocity increase develops individual behaviour dispersion, as suggestive cluster formations begin to emerge.

SwarmOne.PositionThree: Developed emergence of individual clusters, alludes to variations between individual agents position and velocity, thus influence of variables emerges.


SwarmTwo.PositionOne: Increase in central state density, suggests immediate cluster formation, whilst individual position dispersion reflects swarm one.

SwarmTwo.PositionTwo: While the immediate position of individual agents reflects swarm one, as the central velocity increases the relative dispersion suggests a proportional cluster formation.

SwarmTwo.PositionThree: Developing increase in agent’s average velocity suggests position is proportional to time, and therefore behaviour and form is equally proportional.


SwarmThree.PositionOne: Increase of central state density results in quicker emergence of individual agent dispersion, while central behaviour of swarm reflects limited movement.

SwarmThree.PositionTwo: Although velocity and positional development expands cluster formations, the central state of behaviour provides a greater collective swarm about the central origin.

SwarmThree.PositionThree: Development of time frame expands dispersion of agents relative to one another and within clusters supporting general swarm behaviour theory.


SwarmFour.PositionOne: Immediate expansion of individual agents with minimal velocity and position development suggests stray agent’s possible movement is independent.

SwarmFour.PositionTwo: Strayed agents theory is enhanced, as cluster dispersion is based around central perlin axis as relative and proportional position and velocity reflects other swarms.

SwarmFour.PositionThree: Although increased central state density suggests emergence of individual agent cluster dispersion, a central mass remains constant with straying individual agents.

WK4: 12 Experimental Iterations / Images

The following images present experimentation carried out regarding swarm theory. These models are tests of adjusting the variables within grasshopper, and furthermore how successful it would be exporting them to 3ds Max, as each iteration file was between 150-380mb. Thus I was concerned 3ds Max would not be able to handle the import for rendering.

Set One

Set Two


Set Three

Set Four

WK3: Draft Poster

This draft is the layout concept behind my final poster. It consists of an offset title block, a block of spaced iterations, followed by a block of text beneath. Thus keeping the design simple, drawing focus to the work, not the poster layout.

WK3: Poster Design Research

The collection of posters above portrays some research I have carried out regarding poster design. I found these particular examples interesting due to their often simplistic and yet clear manner of presentation. Further I attempted to concentrate on examples presenting multiple iterations as my own will be required to do so, thus studying the manner in which similar items are able to be laid out while remaining to convey the difference between each example.

Image Sources:

1. http://bookstore.web.cmu.edu/MerchDetail.aspx?MerchID=538875

2. http://gizmodo.com/objectified-poster/

3. http://culturepush.com/2009/10/03/spotted-tan-weihao/

4. http://www.designshoot.com/simple-and-minimalist-poster-design-ideas-and-inspiration.html/

5. http://www.spirosxenos.com/archives/21

6. http://www.brandingmagazine.com/2012/02/01/have-you-seen-this-kodak-identity/

7. http://imgfave.com/search/product%20design

8. http://www.wookmark.com/group/1899/posters

9. http://digitalmash.com/work

WK3: Geometric Form Sketches

The collection of sketches above presents some rough conceptual explorations I performed considering possible swarm form variations. Using different brush stroke types I have been able to consider different geometrical interplays of individual agents within the swarm and thus their relative influence upon the remainder of the swarms overall form.

WK2: Tutorial

I decided to look into flocking simulations and similar swarming patterns achieved within Grasshopper and the relative manner in which this is achievable. Thus I came across this tutorial which provided me a possible staring point for producing my final concept.

http://www.youtube.com/watch?v=5ndH_Ih_nso

WK2: Theme Exploration - Research

Research conducted regarding the theme of focus, Swarm Theory has mostly been based upon the variables which define the behaviour and thus form of a swarm. Through which I hope to be able to create a system which uses such variables to define a unique geometrical form evocative of swarm theory.

Conclusions –

According to the C.R. Model, the following variables regarding Swarm form, influence on such are individually weighted –

- An agent’s velocity in relation to another neighbouring agent. Thus intention to match that of the other agents.
- An agent’s location in relation to another neighbouring agent within a pre-defined area. Thus a defined minimum distance.
- A key agent’s relation to the centre of the pre-defined area.
- Density of agent’s within defined space.
- Random external variable, hence a target location.

Through an analysis of self-organising agents, we conclude various natural occurrences –

- A low density swarm mass will see the individual agents swarm a central point, without that point moving.
- A high density swarm mass will see the individual agents move in common direction at a common velocity.

Sources:

J. Boyd, G. Hushlak, C. Jacob, ‘Swarm Art: Interactive art from swarm intelligence’, pp. 628-35 (Unknown Journal).
L. Spector, J. Klein, ‘Evolutionary dynamics discovered via visualization in the breve simulation environment’, pp. 163-170 (Alife VIII: Workshop Proceedings).

J. Klein, ‘Breve: a 3D environment for the simulation of decentralized systems and artificial life’ (Dep. Physical Resource Theory, Chalmers University of Technology and Goteborg University).

H. Kwong, C. Jacob,’ Evolutionary exploration of dynamic swarm behaviour’, pp. 367-74 (2003, IEEE).

J. Gautrais, C. Jost, G. Theraulaz, ‘Key behavioural factors in a self-organised fish school model’, pp. 415.428 (Ann. Zool. Fennici 45).

J. Klein, ‘Continuous 3D agent based simulation in the breve simulation environment’, (Unknown Journal).

B. Garrett, M. Annunziato, A. Pannicelli, C. Liberto, ‘Modelling crowd motion using swarm heuristics and predictive agents’, (Unknown Journal).

WK2: Theme Exploration - Five Images

An image regarding swarm theory which begins to consider the manner in which multiple individual agents’s alignment may define a greater overall form.

This image has been selected as it further develops upon the notion of individual agents defining a greater form, through the consideration of natural alignments within a swarm, hence rows etc.

A conceptual expression of swarm theory, which begins to outline the sense of a greater overall form defined by various individual agents, defined by certain common variables.

Extending on the notion of an overall swarm form constructed through individual agents to consider the manner in which whole swarms may interact with one another.

Beginning to look in a new direction, this image considers a geometrical form defined from swarm theory, however in a sense not defined by individual particle like agents but rather strands.

Image Sources:

1. National Geographic. “Swarm Theory”, (http://ngm.nationalgeographic.com/2007/07/swarms/miller-text, accessed 13.03.2012).
2. Ibid.
3. Ibid.
4. Ibid.
5. Swarm Modelling, “The use of swarm intelligence to generation architectural form”, (http://www.generativeart.com/on/cic/2000/CARRANZA_COATES.HTM, accessed 13.03.2012).

WK1: Three Systems

One: Swarm Theory -

Image Source: http://ngm.nationalgeographic.com/2007/07/swarms/swarms-photography

Swarm theory is a conceptual notion regarding the decentralised, self-organising nature of collective behaviours as a system of interpretation, considering various variables in order to attempt to predict and suggest the continual nature of the ‘swarm’. Variables considering the speculation of movements, distance between the objects of observation or the apparent velocity to one another, or even the relation between swarms, as a result defining a geometrical form, which by considering such variables allows one to understand and contort the swarm from a geometrical point of view.

Two: Light Dispersion -

Image Source: http://www.photostockplus.com/community/tag/ambient-light-underwater-photo-tips/

When referring to this notion of light dispersion, I am in fact referring to the dispersion of light within nature through natural mediums such as water, a fog or even simply a tree, which results in the light itself becoming more visible to the naked eye. Although light is visible in one sense, in another, it simply only exists, however when dispersed through a medium, visible geometrical beams begin to form. This is quite an interesting concept as portrayed through the image above where these geometrical beams are not defined by the individual’s perception, but the dispersion begins to define additional things, such as the gradient colour of the water, dependent upon the medium itself.

Three: Fibonacci Sequence –

Image Source: http://cyberchalky.wordpress.com/2010/03/20/popular-populations-power-or-a-fistful-of-fibonacci/

The Fibonacci sequence in the context here, is referring to its application within natural formations, whether the form of a shell or a flower. However the image I have presented considers the sequence within human form. The image suggests as an individual curls their fist the sequence will emerge through the relative shape portrayed or the number of knuckles visible for example. This is an interesting concept in the sense of a geometrical form defined through a sequence of numbers via the individual perception of the responder as to where the sequence is actually emerging.

WK1: Core Tutorials & Experimentation

Tutorial One

Within this tutorial, I expanded the initial line formation to a polygon through repetition of the original system, before then interconnecting the points via a series of line nodes.

Tutorial Two

Expanding on the original tutorial regarding the formation of various similar lines, I expanded the system to include an additional row of points, before connecting them through proximity nodes, and applying a variably controlled (though a slider) pipe modification.


Tutorial Three

This tutorial, concerning the simple formation of a square via four points, allowed me to begin to understand the process of system simplification, as I was able to reduce the system from nine nodes to four, with the additional ability of variable size control along both the ‘x’ and ‘y’ axis, and the ability to grid the formation.

Tutorial Four

This was a rather simple tutorial concerning line formation again, where to expand on the system I attempted to form a circle, hence a continuous curved line. Once achieved I added a slide so I was able to control the radius of the circle.


Tutorial Five

Expanding on from the simple formation of lines and different polygons, this tutorial began to explore surfacing unique line formations through the loft node. I expanded this tutorial by beginning to consider the analysis nodes within the program, thus in this case reading the surface area.

Tutorial Six

With the introduction of the series node within this tutorial on a two dimensional plane, I expanded the system into the three dimensional field, applying a surface node, controlled through a slider, which allowed me to create various iterations of the form, while further being able to control the initial formation of points through their relative sliders.

Tutorial Seven

Continuing on with the use of series, within this tutorial I expanded the two dimensional plane again into three dimensions, while simplifying the initial layout of points through ‘xy’ sliders, before then further applying a sphere to fit the space formed by the points.

Tutorial Eight

Within this quite complex tutorial concerning the formation of cylinders, with their height controlled by the relative position of a sphere, I replaced the cylinders within lines, interconnecting the various points at the end to create a conceptual surface over the formation, while simplifying part of the control for the sphere from two sliders to one.