"2511","Novelty and Reinforcement Learning in the Value System of Developmental Robots","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.","http://cogprints.org/2511/","Huang, Xiao and Weng, John","Prince, Christopher G. and Demiris, Yiannis and Marom, Yuval and Kozima, Hideki and Balkenius, Christian","       <span class=\"person_name\">Huang, Xiao</span> and <span class=\"person_name\">Weng, John</span>     (2002)  <a href=\"http://cogprints.org/2511/\"><em>Novelty and Reinforcement Learning in the Value System of Developmental Robots.</em></a>       [Conference Paper]           ","","2002"