Value and Reward Based Learning in Neurobots

• Main Author: Jeffrey L. Krichmar (auth)
• Other Authors: Florian Rohrbein (auth)
• Format: Electronic Book Chapter
• Language: English
• Published: Frontiers Media SA 2015
• Series: Frontiers Research Topics
• Subjects: Neurosciences; reward-based learning; basal ganglia; embodied cognition; value system; neurorobotics; action selection; Neuromodulation; reinforcement learning
• Online Access: DOAB: download the publication; DOAB: description of the publication

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. These systems are necessary for an organism to adapt its behavior when an important environmental event occurs. A value system constitutes a basic assumption of what is good and bad for an agent. These value systems have been effectively used in robotic systems to shape behavior. For example, many robots have used models of the dopaminergic system to reinforce behavior that leads to rewards. Other modulatory systems that shape behavior are acetylcholine's effect on attention, norepinephrine's effect on vigilance, and serotonin's effect on impulsiveness, mood, and risk. Moreover, hormonal systems such as oxytocin and its effect on trust constitute as a value system. This book presents current research involving neurobiologically inspired robots whose behavior is: 1) Shaped by value and reward learning, 2) adapted through interaction with the environment, and 3) shaped by extracting value from the environment.