20070827
By extending the horizons of empirical research in biology beyond the territory currently circumscribed by life-as-we-know-it, the study of Artificial Life gives us access to the domain of life-as-it-could-be, and it is within this vastly larger domain that we must ground general theories of biology and in which we will discover novel and practical applications of biology in our engineering endeavors. - Christoph Langton
Children are like tiny flowers: They are varied and need care, but each is beautiful alone and glorious when seen in the community of peers. - Friedrich Froebel
1 Growth Models
In a first exercise we explore different growth models and learn about emergent behavior as it is found in natural, cultural and computational systems.
1.1 Natural
1.1.1 Collect SEM images on the subject of 'growth' including those of seedlings and cellular formation. 1.1.2 Plant a seed (Avocado, Bean, Citrus, Lentil, Sprout, Tomato, ..) Choose the seed that you plant in response to the SEM images that you researched. Use a seed that promises tectonic and structural qualities. Don't shy away from alien morphologies. Take notes of the seed's growth. Keep a diary of the seedling's development.
1.2 Educational
1.2.1 Read Rena Upitis' text "School Architecture and Complexity" 1.2.2 Answer these questions: How does Rena Upitis employ the term "complexity"? What are the three educational models that Rena Upitis refers to? Why did the educator Froebel propose gardens as constructive learning environments? How does Art enter the educational models, that Rena Upitis analyzes?
1.3 Synthetic
1.3.1 Define a simple rule set (axiom) for a Rewriting System. The axiom consists of only three to four characters. Let the system run for nine generations, starting with a seed of only one character. A pattern emerges from your first axiom. 1.3.2 Write several axioms and develop simple mapping rules (2D and 3D) that help visualize and compare the patterns. Possible mapping rules interpret abstract string information as spatial information (e.g. character "A" = move point up one unit). Do not change a rule set while the system is running. Let it run for a set number of generations, map the strings, then evaluate and improve the rules for a new axiom. Test many axioms and develop a set of criteria to evaluate the results. Consider meta rules.
.: Jonas 5:00 PM
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