- author = "Gerd Gruenert",
- title = "Unconventional Programming: Programming Non-programmable Systems",
- school = "Friedrich-Schiller-Universitaet",
- year = "2016",
- address = "Jena, Germany",
- keywords = "genetic algorithms, genetic programming",
-
URL = "
https://www.db-thueringen.de/servlets/MCRFileNodeServlet/dbt_derivate_00038109/thesis.pdf",
- size = "196 pages",
-
abstract = "Unconventional and natural computing research offers
controlled information modification processes in
uncommon media, for example on the molecular scale or
in bacteria colonies. Promising aspects of such systems
are often the non-linear behaviour and the high
connectivity of the involved information processing
components in analogy to neurons in the nervous system.
Unfortunately, such properties make the system behavior
hard to understand, hard to predict and thus also hard
to program with common engineering principles like
modularization and composition, leading to the term of
non-programmable systems. In contrast to many
unconventional computing works that are often focused
on finding novel computing substrates and potential
applications, unconventional programming approaches for
such systems are the theme of this thesis: How can new
programming concepts open up new perspectives for
unconventional but hopefully also for traditional,
digital computing systems?
Mostly based on a model of artificial wet chemical neurons, different unconventional programming approaches from evolutionary algorithms, information theory, self-organization and self-assembly are explored. A particular emphasis is given on the problem of symbol encodings: Often there are multiple or even an unlimited number of possibilities to encode information in the phase space of dynamical systems, e.g. spike frequencies or population coding in neural networks. But different encodings will probably be differently useful, dependent on the system properties, the information transformation task and the desired connectivity to other systems. Hence methods are investigated that can evaluate, analyse as well as identify suitable symbol encoding schemes",
-
notes = "Contents 1 Introduction, 2 Droplet Computers, 3
Evolution of Droplet Computers and Signals, 4
Information Theory Based Methods, 5 Tautological Loops,
6 Embodied Evolution, 7 Programmed Self-Assembly in
Biology
Supervisor: Peter Dittrich",
