Abstract
Value and reward based learning in neurorobots
Highlights
Organisms are equipped with value systems that signal the salience of environmental cues to their nervous system, causing a change in the nervous system that results in modification of their behavior
Jayet Bray and her colleagues developed a neurorobotic system that learned to categorize the valence of speech through positive verbal encouragement, much like a baby would (Jayet Bray et al, 2013)
Their virtual robot, which interacted with a human partner, was controlled by a largescale spiking neuron model of the visual cortex, premotor cortex, and reward system
Summary
Organisms are equipped with value systems that signal the salience of environmental cues to their nervous system, causing a change in the nervous system that results in modification of their behavior. Value systems are often linked to reward systems in neurobiology and in modeling. Their virtual robot, which interacted with a human partner, was controlled by a largescale spiking neuron model of the visual cortex, premotor cortex, and reward system.
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