In 2010, Samsung Electronics and Gatech will create machine learning modules in support of affective behavior, specifically:
A)Using reinforcement (Q-)learning as the basis for adjusting the parameters of TAME and the underlying robotic behaviors, based on direct feedback of the user.
B) Using case-based reasoning (CBR) to store situation-specific affective parameters that can support discontinuous switching of TAME behavior based on user needs and situational requirements.
I am in charge of developing reusable Q-learning component in this project.
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