Genetic Programming of Process Decomposition Strategies for Evolvable Hardware
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{seok:2000:EH,
-
author = "Ho-Sik Seok and Kwang-Ju Lee and Byoung-Tak Zhang and
Dong-Wook Lee and Kwee-Bo Sim",
-
title = "Genetic Programming of Process Decomposition
Strategies for Evolvable Hardware",
-
booktitle = "Proceedings of the Second NASA / DoD Workshop on
Evolvable Hardware",
-
year = "2000",
-
pages = "25--34",
-
address = "Palo Alto, California",
-
publisher_address = "1730 Massachusetts Avenue, N.W., Washington, DC,
20036-1992, USA",
-
month = "13-15 " # jul,
-
organisation = "Jet Propulsion Laboratory, California Institute of
Technology",
-
publisher = "IEEE Computer Society",
-
keywords = "genetic algorithms, genetic programming, EHW,
Intelligent robots, Mobile robots",
-
ISBN = "0-7695-0762-X",
-
DOI = "doi:10.1109/EH.2000.869339",
-
URL = "http://bi.snu.ac.kr/Publications/Conferences/International/EH2000.pdf",
-
size = "10 pages",
-
abstract = "Evolvable hardware is able to offer considerably
higher performance than general-purpose processors and
significantly more flexibility than ASICs. In order to
take the advantages of general-purpose processors and
ASICs, dividing a complex process into subprocesses is
essential. In this paper, we propose an evolutionary
method called context switching that splits a task into
a set of subtasks whose complexity is manageable on the
given hardware. The method is based on genetic
programming. Due to its expressive power, genetic
program can represent flexible strategies for
decomposing complex tasks. The effectiveness of context
switching is demonstrated on the design of adaptive
controllers for a team of autonomous mobile robots.",
-
notes = "EH-2000 XC6216. VCC HOT board. Two Khepera, one object
some obstacles. cannot map environment. context
switching allows process to be bigger than hardware.
Uses fitness switching of
\cite{zhang:1998:fs:ecgbGP}
",
- }
Genetic Programming entries for
Ho-Sik Seok
Kwang-Ju Lee
Byoung-Tak Zhang
Dong-Wook Lee
Kwee-Bo Sim
Citations