Results 271 to 280 of about 6,288,081 (333)

Hard‐Magnetic Soft Millirobots in Underactuated Systems

Advanced Robotics Research, EarlyView.
This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang, Zixuan Zhang, Bingyan Li, Junkai Wang, Hongcheng Gu   +4 more
wiley   +1 more source

Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback

Advanced Robotics Research, EarlyView.
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat, Ali Umut Kaypak, Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami   +4 more
wiley   +1 more source

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

Importance of additional behavioral observation in psychopharmacology: a case study on agomelatine's effects on feedback sensitivity in probabilistic reversal learning in rats. [PDF]

Psychopharmacology (Berl)
Noworyta K, Cieslik-Starkiewicz A, Rygula R.   +2 more
europepmc   +1 more source

Soft Actuators Integrated with Control and Power Units: Approaching Wireless Autonomous Soft Robots

Advanced Robotics Research, EarlyView.
Soft robots exhibit significant development potential in various applications. However, there are still key technical challenges regarding material improvement, structure design and components integration. This review focuses on the development and challenge of soft actuators, power components, and control components in untethered intelligent soft ...
Renwu Shi, Feifei Pan, Xiaobin Ji
wiley   +1 more source

Mitochondrial calcium uniporter deficiency in dentate granule cells remodels neuronal metabolism and impairs reversal learning. [PDF]

J Neurochem
Rose HM, Ferrán B, Ranjit R, Masingale AM, Owen DB, Hussong S, Kinter MT, Galvan V, Logan S, Díaz-García CM.   +9 more
europepmc   +1 more source

Mesencephalic projections to the nucleus accumbens shell modulate value updating during probabilistic reversal learning

Zühlsdorff K, Piller S, Sala-Bayo J, Zhukovsky P, Lamla T, Nissen W, von Heimendahl M, Deiana S, Nicholson JR, Robbins TW, Alsiö J, Dalley JW.   +11 more
europepmc   +1 more source

Neural markers of abstinence in alcohol dependence: Insights from Reward Learning

Komarnyckyj M, Retzler C, Murphy A, Delis I, Fouragnan E.   +4 more
europepmc   +1 more source

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Fractionating adaptive learning: A meta-analysis of the reversal learning paradigm.

Neuroscience and Biobehavioral Reviews, 2019
In constantly changing environments, individuals need to overcome old habitual behaviors in order to learn new associations. Neuroimaging studies have focused on prediction errors, reversal errors and reversal switching in the reversal learning paradigm.
Z. Yaple, Rongjun Yu
semanticscholar   +3 more sources

Reversal Learning

Encyclopedia of Autism Spectrum Disorders, 2021
K. Lionello-DeNolf
semanticscholar   +2 more sources