Manual Engineering and Evolution of Emergent Algorithms for Agents on Two-dimensional Grids

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@PhdThesis{MarcusKomannDissertation,
  author =       "Marcus Komann",
  title =        "Manual Engineering and Evolution of Emergent
                 Algorithms for Agents on Two-dimensional Grids",
  school =       "Erlangen",
  year =         "2010",
  type =         "Doktor-Ingenieur",
  address =      "Germany",
  month =        "22 " # dec,
  keywords =     "genetic algorithms, genetic programming, EHW, FPGA,
                 agent, evolution, emergence, deterministic finite state
                 machine, field programmable gate array, feature
                 extraction, smart camera",
  URL =          "http://www.opus.ub.uni-erlangen.de/opus/volltexte/2011/2315",
  URL =          "http://www.opus.ub.uni-erlangen.de/opus/volltexte/2011/2315/pdf/MarcusKomannDissertation.pdf",
  size =         "292 pages",
  abstract =     "In this thesis, the problem of detecting the
                 attributes of multiple objects in binary images in
                 realtime is solved. It is a common problem in
                 industrial machine vision. For the solution, the usage
                 of emergent algorithms on a smart camera with a
                 fine-grained massively-parallel processor is proposed.
                 Combining both is promising since such processors can
                 exploit the abilities of emergent algorithms.
                 Therefore, so-called Marching Pixels are introduced.
                 These are local agents that traverse the pixel grid of
                 an image in a certain way in order to accumulate global
                 data about the image objects. At first, manually
                 engineered Marching Pixels algorithms for different
                 object classes are presented and compared. Afterwards,
                 their realisations in hardware are shown. These
                 realizations are able to fulfil the real time
                 requirements and are small enough for application in
                 real industrial scenarios. They can further be used to
                 execute other emergent algorithms that are based on 2-D
                 grids. However, the absolute quality of the manually
                 engineered algorithms is unknown. In the thesis,
                 emergent agent algorithms for 2-D grids are thus also
                 evolved. First, the effectiveness of evolution for
                 finding good emergent agent algorithms is shown. Then,
                 it is argued that improving agent abilities has to be
                 done by cautiously balancing increased agent amounts
                 and higher agent intelligence. The focus on the initial
                 machine vision problem is thereby expanded to emergent
                 agents on 2-D grids in general since many complex
                 systems today comprise such entities and controlling
                 their emergent phenomena is difficult but worthwhile.",
  notes =        "Some consideration of GP in later chapters.

                 Advisor: Fey, Dietmar (Prof. Dr.-Ing.)",
}

Genetic Programming entries for Marcus Komann

Citations