Results 291 to 300 of about 5,721,941 (348)

Development of an imitation learning method for a neural network system of mobile robot’s movement on example of the maze solving

T. Yu. Kim, Ryhor Prakapovich
openalex   +2 more sources

What imitating an iconic robot reveals on allospecific vocal imitation in parrots and starlings. [PDF]

Sci Rep
Dam NCP, Honing H, Spierings MJ.
europepmc   +1 more source

On the origin of the reward function: Exploring the role of conditioned reinforcement and social learning. [PDF]

Psychon Bull Rev
Rigoli F.
europepmc   +1 more source

Effects of intention understanding and brief imitative experience on the mirror neuron system: An EEG study using Japanese sign language. [PDF]

PLoS One
Osaki T, Minamoto T.
europepmc   +1 more source

LEARNING A REPRESENTATION OF A BELIEVABLE VIRTUAL CHARACTER’S ENVIRONMENT WITH AN IMITATION ALGORITHM

, 2013
Fabien Tencé, Cédric Buche, Olivier Marc, Pierre De Loor   +3 more
openalex   +1 more source

Evaluating Computerised Assessment of Motor Imitation (CAMI) for identifying autism-specific difficulties not observed for attention-deficit hyperactivity disorder or neurotypical development. [PDF]

Br J Psychiatry
Santra R, Pacheco C, Crocetti D, Vidal R, Mostofsky SH, Tunçgenç B.   +5 more
europepmc   +1 more source

Body Knowledge and Emotion Recognition in Preschool Children: A Comparative Study of Human Versus Robot Tutors. [PDF]

Behav Sci (Basel)
Araguas A, Blanchard A, Derégnaucourt S, Chopin A, Guellai B.   +4 more
europepmc   +1 more source

Think aloud imitation learning

, 2006
openaire   +2 more sources

Some of the next articles are maybe not open access.

Related searches:

Hierarchical Interpretable Imitation Learning for End-to-End Autonomous Driving

IEEE Transactions on Intelligent Vehicles, 2023
End-to-end autonomous driving provides a simple and efficient framework for autonomous driving systems, which can directly obtain control commands from raw perception data.
Siyu Teng, Long Chen, Yunfeng Ai, Yuanye Zhou, Zhe Xuanyuan, Xuemin Hu   +5 more
semanticscholar   +1 more source

Decomposing the Generalization Gap in Imitation Learning for Visual Robotic Manipulation

IEEE International Conference on Robotics and Automation, 2023
What makes generalization hard for imitation learning in visual robotic manipulation? This question is difficult to approach at face value, but the environment from the perspective of a robot can often be decomposed into enumerable factors of variation ...
Annie Xie, Lisa Lee, Ted Xiao, Chelsea Finn   +3 more
semanticscholar   +1 more source