Frontiers in Evolutionary Robotics / / edited by Hitoshi Iba.

This book presented techniques and experimental results which have been pursued for the purpose of evolutionary robotics. Evolutionary robotics is a new method for the automatic creation of autonomous robots. When executing tasks by autonomous robots, we can make the robot learn what to do so as to...

Full description

Saved in:
Bibliographic Details
TeilnehmendeR:
Place / Publishing House:Croatia : : IntechOpen,, 2007.
Year of Publication:2008
2007
Language:English
Physical Description:1 online resource (598 pages)
Tags: Add Tag
No Tags, Be the first to tag this record!
id 993547659204498
ctrlnum (CKB)3230000000075289
(NjHacI)993230000000075289
(oapen)https://directory.doabooks.org/handle/20.500.12854/64672
(EXLCZ)993230000000075289
collection bib_alma
record_format marc
spelling Iba, Hitoshi edt
Frontiers in Evolutionary Robotics / edited by Hitoshi Iba.
IntechOpen 2008
Croatia : IntechOpen, 2007.
1 online resource (598 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Description based on publisher supplied metadata and other sources.
This book presented techniques and experimental results which have been pursued for the purpose of evolutionary robotics. Evolutionary robotics is a new method for the automatic creation of autonomous robots. When executing tasks by autonomous robots, we can make the robot learn what to do so as to complete the task from interactions with its environment, but not manually pre-program for all situations. Many researchers have been studying the techniques for evolutionary robotics by using Evolutionary Computation (EC), such as Genetic Algorithms (GA) or Genetic Programming (GP). Their goal is to clarify the applicability of the evolutionary approach to the real-robot learning, especially, in view of the adaptive robot behavior as well as the robustness to noisy and dynamic environments. For this purpose, authors in this book explain a variety of real robots in different fields. For instance, in a multi-robot system, several robots simultaneously work to achieve a common goal via interaction; their behaviors can only emerge as a result of evolution and interaction. How to learn such behaviors is a central issue of Distributed Artificial Intelligence (DAI), which has recently attracted much attention. This book addresses the issue in the context of a multi-robot system, in which multiple robots are evolved using EC to solve a cooperative task. Since directly using EC to generate a program of complex behaviors is often very difficult, a number of extensions to basic EC are proposed in this book so as to solve these control problems of the robot.
English
Robotics.
Automatic control engineering
3-902613-19-X
Iba, Hitoshi, editor.
language English
format eBook
author2 Iba, Hitoshi,
author_facet Iba, Hitoshi,
author2_variant h i hi
h i hi
author2_role TeilnehmendeR
title Frontiers in Evolutionary Robotics /
spellingShingle Frontiers in Evolutionary Robotics /
title_full Frontiers in Evolutionary Robotics / edited by Hitoshi Iba.
title_fullStr Frontiers in Evolutionary Robotics / edited by Hitoshi Iba.
title_full_unstemmed Frontiers in Evolutionary Robotics / edited by Hitoshi Iba.
title_auth Frontiers in Evolutionary Robotics /
title_new Frontiers in Evolutionary Robotics /
title_sort frontiers in evolutionary robotics /
publisher IntechOpen
IntechOpen,
publishDate 2008
2007
physical 1 online resource (598 pages)
isbn 953-51-5829-5
3-902613-19-X
callnumber-first T - Technology
callnumber-subject TP - Chemical Technology
callnumber-label TP242
callnumber-sort TP 3242 F766 42007
illustrated Not Illustrated
dewey-hundreds 600 - Technology
dewey-tens 620 - Engineering
dewey-ones 629 - Other branches of engineering
dewey-full 629.892
dewey-sort 3629.892
dewey-raw 629.892
dewey-search 629.892
work_keys_str_mv AT ibahitoshi frontiersinevolutionaryrobotics
status_str n
ids_txt_mv (CKB)3230000000075289
(NjHacI)993230000000075289
(oapen)https://directory.doabooks.org/handle/20.500.12854/64672
(EXLCZ)993230000000075289
carrierType_str_mv cr
is_hierarchy_title Frontiers in Evolutionary Robotics /
author2_original_writing_str_mv noLinkedField
_version_ 1787548669147348992
fullrecord <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00859nam a2200277 i 4500</leader><controlfield tag="001">993547659204498</controlfield><controlfield tag="005">20221014135245.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr |||||||||||</controlfield><controlfield tag="008">221014s2007 ci o 000 0 eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">953-51-5829-5</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)3230000000075289</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(NjHacI)993230000000075289</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(oapen)https://directory.doabooks.org/handle/20.500.12854/64672</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)993230000000075289</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">NjHacI</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="c">NjHacl</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">TP242</subfield><subfield code="b">.F766 2007</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">629.892</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Iba, Hitoshi</subfield><subfield code="4">edt</subfield></datafield><datafield tag="245" ind1="0" ind2="0"><subfield code="a">Frontiers in Evolutionary Robotics /</subfield><subfield code="c">edited by Hitoshi Iba.</subfield></datafield><datafield tag="260" ind1=" " ind2=" "><subfield code="b">IntechOpen</subfield><subfield code="c">2008</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Croatia :</subfield><subfield code="b">IntechOpen,</subfield><subfield code="c">2007.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (598 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This book presented techniques and experimental results which have been pursued for the purpose of evolutionary robotics. Evolutionary robotics is a new method for the automatic creation of autonomous robots. When executing tasks by autonomous robots, we can make the robot learn what to do so as to complete the task from interactions with its environment, but not manually pre-program for all situations. Many researchers have been studying the techniques for evolutionary robotics by using Evolutionary Computation (EC), such as Genetic Algorithms (GA) or Genetic Programming (GP). Their goal is to clarify the applicability of the evolutionary approach to the real-robot learning, especially, in view of the adaptive robot behavior as well as the robustness to noisy and dynamic environments. For this purpose, authors in this book explain a variety of real robots in different fields. For instance, in a multi-robot system, several robots simultaneously work to achieve a common goal via interaction; their behaviors can only emerge as a result of evolution and interaction. How to learn such behaviors is a central issue of Distributed Artificial Intelligence (DAI), which has recently attracted much attention. This book addresses the issue in the context of a multi-robot system, in which multiple robots are evolved using EC to solve a cooperative task. Since directly using EC to generate a program of complex behaviors is often very difficult, a number of extensions to basic EC are proposed in this book so as to solve these control problems of the robot.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">English</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Robotics.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Automatic control engineering</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">3-902613-19-X</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Iba, Hitoshi,</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="906" ind1=" " ind2=" "><subfield code="a">BOOK</subfield></datafield><datafield tag="ADM" ind1=" " ind2=" "><subfield code="b">2023-02-22 03:16:52 Europe/Vienna</subfield><subfield code="f">system</subfield><subfield code="c">marc21</subfield><subfield code="a">2012-12-09 08:17:33 Europe/Vienna</subfield><subfield code="g">false</subfield></datafield><datafield tag="AVE" ind1=" " ind2=" "><subfield code="i">DOAB Directory of Open Access Books</subfield><subfield code="P">DOAB Directory of Open Access Books</subfield><subfield code="x">https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&amp;portfolio_pid=5338610350004498&amp;Force_direct=true</subfield><subfield code="Z">5338610350004498</subfield><subfield code="b">Available</subfield><subfield code="8">5338610350004498</subfield></datafield></record></collection>