Results 31 to 40 of about 5,721,941 (348)
Motion Generation Using Bilateral Control-Based Imitation Learning With Autoregressive Learning
IEEE Access, 2021 Imitation learning has been studied as an efficient and high-performance method to generate robot motion. Specifically, bilateral control-based imitation learning has been proposed as a method of realizing fast motion.
Ayumu Sasagawa +2 more
doaj +1 more source
Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations [PDF]
International Conference on Machine Learning, 2022 We study the problem of offline Imitation Learning (IL) where an agent aims to learn an optimal expert behavior policy without additional online environment interactions. Instead, the agent is provided with a supplementary offline dataset from suboptimal
Haoran Xu, Xianyuan Zhan
semanticscholar +1 more source
Imitation of Peers in Children and Adults
Games, 2018 Imitation of the successful choices of others is a simple and superficially attractive learning rule. It has been shown to be an important driving force for the strategic behavior of (young) adults. In this study we examine whether imitation is prevalent
Jose Apesteguia +4 more
doaj +1 more source
Re-examination of Oostenbroek et al. (2016): evidence for neonatal imitation of tongue protrusion [PDF]
, 2017 The meaning, mechanism, and function of imitation in early infancy have been actively discussed since Meltzoff and Moore's (1977) report of facial and manual imitation by human neonates. Oostenbroek et al. (2016) claim to challenge the existence of early
Anisfeld +34 more
core +5 more sources
Deep Reinforcement Learning Task Assignment Based on Domain Knowledge
IEEE Access, 2022 Deep Reinforcement Learning (DRL) methods are inefficient in the initial strategy exploration process due to the huge state space and action space in large-scale complex scenarios.
Jiayi Liu +4 more
doaj +1 more source
Rage Against the Machines: How Subjects Learn to Play Against Computers [PDF]
, 2005 We use an experiment to explore how subjects learn to play against computers which are programmed to follow one of a number of standard learning algorithms.
Dürsch, Peter +3 more
core +6 more sources
What Matters in Language Conditioned Robotic Imitation Learning Over Unstructured Data [PDF]
IEEE Robotics and Automation Letters, 2022 A long-standing goal in robotics is to build robots that can perform a wide range of daily tasks from perceptions obtained with their onboard sensors and specified only via natural language.
Oier Mees +2 more
semanticscholar +1 more source
Children, 2022 Across cultures, imitation provides a crucial route to learning during infancy. However, neural predictors which would enable early identification of infants at risk of suboptimal developmental outcomes are still rare.
Laura Katus +11 more
doaj +1 more source
Frontiers in Psychology, 2015 Children are exceptional, even ‘super’ imitators, but comparatively poor independent problem-solvers or innovators. However, human cultural evolution depends on both imitation and innovation.
Francys eSubiaul +3 more
doaj +1 more source
Hybrid Trajectory and Force Learning of Complex Assembly Tasks: A Combined Learning Framework
IEEE Access, 2021 Complex assembly tasks involve nonlinear and low-clearance insertion trajectories with varying contact forces at different stages. For a robot to solve these tasks, it requires a precise and adaptive controller which conventional force control methods ...
Yan Wang +3 more
doaj +1 more source