Tactile Reinforcement Learning
Tactile Reinforcement Learning is a machine learning framework that integrates tactile sensory feedback into the reinforcement learning paradigm to enable agents to learn goal-directed manipulation behaviors through physical interaction with environments, distinguished by its reliance on haptic input as a primary source of state information for decision-making.
5
Publications
289
Citations
16
Authors
7
Institutions
Publications per year
2017–2026
2
Parents
5
Using Technology to Support STEM Reading
M. H. Schneps, Jamie K. O'Keeffe, Amanda Heffner-Wong et al. · Journal of Special Education Technology · 2010 · 35 citations
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Google DeepMind (United Kingdom)
London, United Kingdom
1 h-index
1 publications
33 citations
Freie Universität Berlin
Berlin, Germany
1 h-index
2 publications
362 citations
Bristol Robotics Laboratory
Bristol, United Kingdom
1 h-index
3 publications
99 citations
Google (United Kingdom)
London, United Kingdom
1 h-index
1 publications
33 citations
Center for Astrophysics Harvard & Smithsonian
Cambridge, United States
1 h-index
4 publications
140 citations
Technische Universität Berlin
Berlin, Germany
1 h-index
3 publications
543 citations
Friedrich-Wilhelm-Bessel-Institut Forschungsgesellschaft
Bremen, Germany
1 h-index
3 publications
84 citations

Sejong University
Seoul, South Korea
1 publications
11 citations
1–8 of 7
1 publications · 33 citations
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1 publications · 28 citations
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1 publications · 12 citations
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1 publications · 181 citations
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JSET · 1 publications · 35 citations
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