%A Xiao Huang
%A John Weng
%T Novelty and Reinforcement Learning in the Value System of Developmental Robots
%X The value system of a developmental robot signals the occurrence of salient sensory inputs, modulates the mapping from sensory inputs to action outputs, and evaluates candidate actions. In the work reported here, a low level value system is modeled and implemented. It simulates the non-associative animal learning mechanism known as habituation effect. Reinforcement learning is also integrated with novelty. Experimental results show that the proposed value system works as designed in a study of robot viewing angle selection.
%K developmental robot, value system, sensory, habituation effect, reinforcement learning, IHDR, SAIL
%P 47-55
%E Christopher G. Prince
%E Yiannis Demiris
%E Yuval Marom
%E Hideki Kozima
%E Christian Balkenius
%V 94
%D 2002
%I Lund University Cognitive Studies
%L cogprints2511

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