Introduction to AI Robotics
The Journal of Machine Learning Research
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Control Architecture for Human–Robot Integration: Application to a Robotic Wheelchair
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Reflexes are meant to provide animals with automatic responses for a better adaptation to their niches. In particular, humans have the capability to voluntarily modify these responses in certain situations to attain specific goals. The ability of using past experiences to tune automatic responses (reflexes) has contributed to a better adaptation to our environments and thus, the question arises of applying this to machines. In the robotic arena, imitating animal reflexes has been largely explored through fixed stimuli-behavior schemas included in reactive or hybrid architectures. In this paper we consider the less explored direction of permitting a mobile robot to modify its reflexes according to its experience, i.e. ignoring the reflex of stopping when approaching an obstacle if the robot goal is close. We explore reinforcement learning as a mechanism to automatically learn when and how modulate reflexes over the robot operational life. Advantages of our mechanism are illustrated in simulations.