C.M. Fernandes12

C. Isidoro2

F. Barata2

J.J. Merelo1

A.C. Rosa2

From Pherographia to Color Pherographia

Color Sketching with Artificial Ants

1University of Granada2Technical University of Lisbon

Summary

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The Ant System: from Chialvo and Millonas’s Ant Model to Pherographia. Artwork created with monochromatic pherographia. Color Pherographia (four variations). Results. Conclusions and future work.

Original b/w photo Pheromone density after 100 iterations

Ants after 100 iterations

The Original Model

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Dante Chialvo and Mark Millonas, How Ants Build Cognitive Maps, 1995 The model simulates a swarm of ants moving in an homogeneous environment.

A population of ants is randomly distributed in a two-dimensional array. The ants move one step (cell) in each iteration, following simple rules.

Global and complex behaviour emerges from the simple rules and from the indirect interaction of the ants via the environment.

Self-Organization Stigmergy Simple ((local, no explicit memory,

homogeneous and isotropic)

The Original Model (Chialvo and Milonas)

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Pheromone weighting function:

1

1W

Normalised Transition probabilities (probability to go from cell k to cell i)

kj jj

iiik wW

wWP

Pheromone deposition rate: T= η

increasing the cell’s pheromone density σ

β: degree of randomness with which the ants follow the pheromone gradientδ: saturation effect, ant’s ability to sense pheromone decreases at high concentrations

w = 1/12

w = 1/4

w = 1/2w = 1/2

w = 1/20

w = 1

w = 1/4

w = 1/12

Evaporation: pheromone density in each cell is decreased by a constant amount.

The Original Model

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Ramos and Almeida’s Model

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- Instead of constant pheromone deposition rate, a term not constant is included:

cmpT

Gives a measure of similaritybetween two different lattice

windows, in terms of grey levelspatial arrangement.

Constant

Ramos and Almeida, Artificial Ant Colonies in Digital Images Habitat, ANTS 2000

Final Model

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An “evolutionary” component is added to the ant system.Each ants has an initial energy that decreases in each time step:

the probability of surviving depends on the energy: P = 1-e(a)Each ant is allowed to reproduce in each time step. The

reproduction probability depends on the number of neighbouring ants and the pheromone density.

Fernandes, Ramos and Rosa, Self-Regulated Artificial Ant Colonies on Digital Image Habitats, International Journal of Lateral Computing, 2005

)max

)1((*)(

gl

gl

r nWP

W(0) = W(8) =0; W(4) = 1; W(5) = W(3) =0.75; W(6) = W(2) =0.5; W(7) = W(1) = 0.25.

Timor Mortis Conturbat Me (2008)

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“Timor Mortis...” was exhibited at the P4Photography art gallery, in Lisbon.About this work: http://carlosmfernandes.com/index_archivos/Page768.htm

Eadweard Muybridge (1830-1904)

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The Horse and the Ants (2009)

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The Horse and the Ants has been exhibited in several art and science shows.

Criatividade Computacional, ISCTE, Abril de 2010

11

Studies for a Modern Zoetrope (2011)

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Becher’s typologies: analysis and synthesis

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Bernd e Hilla Becher

Idris Kahn

Becher’s tipologies: analysis and synthesis

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Color Pherography

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The main difference is the equation:

cmpT In b/w pherography, ∆ measures the contrast in the region around the ant’s position.

In color pherography: First, RBG is converted to L, a and b (Lab color space)

L measures the lightness a and b measure the color.

∆ is the Euclidean distance between the average of L, a and b, each averaged over the cell and its 8 neighborig cells, and the average of L, a and b averaged over the previous cell and its 8 neighboring cells.

Color Pherography

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Four variations were tested, each one with different rules for the ants movements and for handling occupied cells

Originally, the objective was to remove a bias introduced by constraint of having no more than one ant in each cell.

Color Pherography

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Variation 1: when an ant tries to move to an occupied cell, the ant that occupies that cell is moved in the same direction and its directional vector changes.

Color Pherography

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Variation 2: the ants are not allowed to move to occupied cells. If one tries to move to an occupied cell, it will stop, and the direction of the ant occupying that cell changes to that of the vectorial sum between the original direction and the one towards which this ant tried to move.

Color Pherography

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Variation 3: ants “bounce off” if they try to move to occupied cells.

Color Pherography

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Variation 4: introduces speed and implements ants with variable speed, that is, the speed may change when an ant moves to a cell occupied by another ant.

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Conclusions and Future Work

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The monochromatic pherographia has been extended to color pherographia.

Color pherographia also detects the edges of the image.

Investigate other local and simple rules that generate different global behaviour.

Emergence, memory and readaptation (videos).

Implement pherographia (B/W and color) in a digital camera using LUA programming language.