説明
Behavior generation in humans and animals usually employs a combination of bottom-up and top-down patterns. Most available robotic architectures utilize either bottom-up or top-down activation including hybrid architectures. In this paper, we propose a behavior generation mechanism that can seamlessly combine these two strategies. One of the main advantages of the proposed approach is that it can naturally combine both bottom-up and top-down behavior generation mechanisms which can produce more natural behavior. This is achieved by utilizing results from the theory of simulation in neuroscience which tries to model the mechanism used in human infants to develop a theory of mind. The proposed approach was tested inmodeling spontaneous gaze control during natural face to face interactions and provided more natural, human-like behavior compared with a state-of-the-art gaze controller that utilized a bottom-up approach.