2018
DOI: 10.3389/fnbot.2018.00019
|View full text |Cite
|
Sign up to set email alerts
|

Variety Wins: Soccer-Playing Robots and Infant Walking

Abstract: Although both infancy and artificial intelligence (AI) researchers are interested in developing systems that produce adaptive, functional behavior, the two disciplines rarely capitalize on their complementary expertise. Here, we used soccer-playing robots to test a central question about the development of infant walking. During natural activity, infants' locomotor paths are immensely varied. They walk along curved, multi-directional paths with frequent starts and stops. Is the variability observed in spontane… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
29
0

Year Published

2018
2018
2024
2024

Publication Types

Select...
7
3

Relationship

4
6

Authors

Journals

citations
Cited by 65 publications
(30 citation statements)
references
References 41 publications
(44 reference statements)
0
29
0
Order By: Relevance
“…Artificial Intelligence researchers have experimentally tested this hypothesis using simulated humanoid walkers. When trained on varied paths (Ossmy et al., ; Urieli, MacAlpine, Kalyanakrishnan, Bentor, & Stone, ) or in varied environments (Heess et al., ), simulated walkers perform better in new, untrained settings. Here, we find that toys designed to encourage locomotion prompt infants to cover more ground.…”
Section: Discussionmentioning
confidence: 99%
“…Artificial Intelligence researchers have experimentally tested this hypothesis using simulated humanoid walkers. When trained on varied paths (Ossmy et al., ; Urieli, MacAlpine, Kalyanakrishnan, Bentor, & Stone, ) or in varied environments (Heess et al., ), simulated walkers perform better in new, untrained settings. Here, we find that toys designed to encourage locomotion prompt infants to cover more ground.…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, immense varied input is conducive for learning. Simulated robots trained on infant-like paths or in varied environments perform better in new, untrained settings [59–61].…”
Section: Suggestions For Developmental Researchmentioning
confidence: 99%
“…Researchers could use simulations to test whether the way a person planned and executed their movements was functional or not. Along these lines, Ossmy et al ( 2018 ) trained soccer-playing robots with kinematic walking data generated by infants during free play. The robots trained with a high variance of kinematic patterns won the simulated season of “RoboCup” (Ossmy et al, 2018 ) against robots trained with a low variance of kinematics.…”
Section: Future Research Directions and Potential Applications Of Embodied Planningmentioning
confidence: 99%