Bio-inspired Reflex System for Learning Visual Information for Resilient Robotic Manipulation
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The effects of practice schedule on learning a complex judgment task were investigated. In Experiment 1, participants' judgment accuracy on a retention test was higher after a random practice schedule than after a blocked schedule or operational schedule. ...
Perceptual learning is reward-based. A recent mathematical analysis showed that any reward-based learning system can learn two tasks only when the mean reward is identical for both tasks [Frémaux, Sprekeler and Gerstner, 2010, The Journal of Neuroscience, ...
In motor learning, training a task B can disrupt improvements of performance of a previously learned task A, indicating that learning needs consolidation. An influential study suggested that this is the case also for visual perceptual learning [1]. Using t ...
Reinforcement learning in neural networks requires a mechanism for exploring new network states in response to a single, nonspecific reward signal. Existing models have introduced synaptic or neuronal noise to drive this exploration. However, those types o ...
We consider the problem of learning robust models of robot motion through demonstration. An approach based on Hidden Markov Model (HMM) and Gaussian Mixture Regression (GMR) is proposed to extract redundancies across multiple demonstrations, and build a ti ...
Automatically synthesizing behaviors for robots with articulated bodies poses a number of challenges beyond those encountered when generating behaviors for simpler agents. One such challenge is how to optimize a controller that can orchestrate dynamic moti ...
Acute stress regulates different aspects of behavioral learning through the action of stress hormones and neuromodulators. Stress effects depend on stressor's type, intensity, timing, and the learning paradigm. In addition, genetic background of animals mi ...
Perceptual learning is the ability to improve perception through practice. Perceptual learning is usually specific for the task and features learned. For example, improvements in performance for a certain stimulus do not transfer if the stimulus is rotated ...
Perceptual learning is learning to perceive and is essential for all forms of perception and learning. For a long time it was believed that perceptual learning was a simple process suitable as a model for studying general mechanism of learning. Researchers ...
Abstract The paper presents a two-layered system for (1) learning and encoding a periodic signal without any knowledge on its frequency and waveform, and (2) modulating the learned periodic trajectory in response to external events. The system is used to l ...