Research

Evolutionary Optimization in Biology and Numerics by Abstraction and Synthesis of Natural Organisms" Behavior

Evolution

The project touches a variety of neighboring disciplines. Especially numerical mathematics and a kind of abstracted evolutionary biology have effects on the project. Evolutionary processes are synthesized on simple organism which have abstract abilities (like eating, growing, producing offspring ...). These abilities will be governed by simple rule sets (like if-clauses or Lindenmayer-systems) and by the (phenotypical) struggle for food. Food (or energy) is the preliminary for the individuals taking different actions.

During evolution on these rule-sets different species will show up. They will compete for food on artificial landscapes, and become species in different niches of the landscapes. Because they can grow, they search food in different regions, implying that by knowing a fast way to globally good regions of the landscape makes an individual perform well in the competition against the other members of a population.

Going on in this metaphor, individuals should emerge performing well as global optimizers of some target functions. And this is the point where to return to numerical mathematics.

This kind of Evolutionary Algorithm (Genetic Programming on Syntactical Structures) works on a meta level. It will not optimize on its own, it evolves optimizing individuals. This process as well as the optimizing performance of the resulting individuals have to be examined.

Remarkable about the Evolutionary Process is the fact that we will try to exclude any central "god" who has an exogeneous target function in his hands measuring the optimizing individuals. Local competition will be the key for that.