2014 IEEE International Conference on Evolvable Systems 2014
DOI: 10.1109/ices.2014.7008736
|View full text |Cite
|
Sign up to set email alerts
|

A robotic ecosystem with evolvable minds and bodies

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
17
0

Year Published

2015
2015
2023
2023

Publication Types

Select...
5
1
1

Relationship

1
6

Authors

Journals

citations
Cited by 14 publications
(17 citation statements)
references
References 29 publications
0
17
0
Order By: Relevance
“…However, physically realistic simulations of robot populations have to contend with severe limitations of present-day simulators that struggle to simulate more than a couple of dozen individuals of moderate complexity [9]. We expect that the study of the dynamics of evolution, in particular the interplay between the development of controller and morphology benefits greatly from simulations with larger populations, numbering hundreds or even thousands of individuals.…”
Section: Geccomentioning
confidence: 99%
See 1 more Smart Citation
“…However, physically realistic simulations of robot populations have to contend with severe limitations of present-day simulators that struggle to simulate more than a couple of dozen individuals of moderate complexity [9]. We expect that the study of the dynamics of evolution, in particular the interplay between the development of controller and morphology benefits greatly from simulations with larger populations, numbering hundreds or even thousands of individuals.…”
Section: Geccomentioning
confidence: 99%
“…Request permissions from permissions@acm.org. by measuring competence in some task but depends solely on robots behaving so that they survive and spread their genes as the environment allows [8,9]. Such an ecosystem enables research into the evolution of mind and body in a new way and offers profound opportunities for novel research in artificial life and embodied artificial intelligence with implications for evolutionary robotics and evolutionary biology [5,3].…”
Section: Introductionmentioning
confidence: 99%
“…Genotype representations in the literature use binary [36][37][38], integer [39], real number [40][41][42] and string [43] encoding with many applying either or a combination of the different encoding methods. The basic genome types could also be placed in a matrix [44], vector [34,[45][46][47], graph [48][49][50][51][52][53] and tree [54][55][56][57][58][59][60][61][62].…”
Section: Genotypementioning
confidence: 99%
“…The basic genome types could also be placed in a matrix [44], vector [34,[45][46][47], graph [48][49][50][51][52][53] and tree [54][55][56][57][58][59][60][61][62]. Further, in other representations, [34,63] applied the concept of a hox gene for encoding body morphology and [39,64] applied Compositional Pattern-Producing Networks (CPPN) based encoding . The CPPN encoding involves accepting arguments as inputs and generating a resultant graph which explains the connections between various functions.…”
Section: Genotypementioning
confidence: 99%
See 1 more Smart Citation