Results 221 to 230 of about 96,046 (256)

"We learn while doing": informal training experiences of critical care nurses managing dialysis technologies in intensive care units. [PDF]

BMC Nurs
Almulhim MY, Fakhry SF.
europepmc   +1 more source

Large Language Model Adaptation Strategies in Speech-Based Cognitive Screening: Systematic Evaluation. [PDF]

JMIR AI
Taherinezhad F, Momeni Nezhad MJ, Karimi S, Rashidi S, Zolnour A, Dadkhah M, Haghbin Y, Azadmaleki H, Zolnoori M.   +8 more
europepmc   +1 more source

Serious learning through play: a decade of the Self-Directed Learning Playground. [PDF]

Korean J Med Educ
Sow CF.
europepmc   +1 more source

Enhancing online teaching of "subgingival scaling and root planing" through periodontal endoscopy assistance: a study on its application in a teaching-practicing module. [PDF]

BMC Oral Health
Yu H, Li J, Jia Y, Zhang J, Wang Z, Zou H.   +5 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Skill Demonstration Transfer for Learning from Demonstration

Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction Extended Abstracts, 2015
Learning from Demonstration is an effective method for interactively teaching skills to a robot learner. However, a skill learned via demonstrations is often learned within a particular environment and uses a specific set of objects, and thus may not be immediately applicable for use in unfamiliar environments.
Tesca Fitzgerald, Andrea Lockerd Thomaz
openaire   +1 more source

Learning from Corrective Demonstrations

2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2019
Robots deployed in human environments will inevitably encounter unmodeled scenarios which are likely to result in execution failures. To address this issue, we would like to allow co-present naive users to correct and improve the robot's behavior as these edge cases are encountered over time.
Reymundo A. Gutierrez, Elaine Schaertl Short, Scott Niekum, Andrea Lockerd Thomaz   +3 more
openaire   +1 more source

Objective learning from human demonstrations

Annual Reviews in Control, 2021
Abstract Researchers in biomechanics, neuroscience, human–machine interaction and other fields are interested in inferring human intentions and objectives from observed actions. The problem of inferring objectives from observations has received extensive theoretical and methodological development from both the controls and machine learning ...
Jonathan Feng-Shun Lin, Pamela Carreno-Medrano, Mahsa Parsapour, Maram Sakr, Dana Kulic   +4 more
openaire   +1 more source

Learning from Demonstration in Spatial Exploration

Proceedings of the AAAI Conference on Artificial Intelligence, 2011
We present the initial stage of our research on Learning from Demonstration algorithms. We have implemented an algorithm based on Confident Execution, one of the components of the Confidence-Based Autonomy algorithm developed by Chernova and Veloso.
Ozgelen, A.T., Munoz, J.P., Sklar, Elizabeth   +2 more
openaire   +2 more sources

Introspective Reinforcement Learning and Learning from Demonstration

International Joint Conference on Autonomous Agents and Multiagent Systems, 2018
Reinforcement learning is a paradigm to model how an autonomous agent learns to maximise its cumulative reward by interacting with the environment. One challenge faced by reinforcement learning is that in many environments the reward signal is sparse, leading to slow improvement of the agent's performance in early learning episodes.
Mao Li, Tim Brys, Daniel Kudenko
openaire   +2 more sources

Learning from Demonstration

2015
Creating robots that can easily learn new skills as effectively as humans (or dogs or ants) is the holly grail of intelligent robotics. Several approaches to achieve this goal have appeared over the years.
Yasser Mohammad, Toyoaki Nishida
openaire   +1 more source