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From Deliberative to Routine Behaviors: A Cognitively Inspired Action-Selection Mechanism for Routine Behavior Capture

Computer Science Department, Carnegie Mellon University, soniac{at}cs.cmu.edu

Ronald C. Arkin

College of Computing, Georgia Institute of Technology, arkin{at}cc.gatech.edu

Long-term human—robot interaction, especially in the case of humanoid robots, requires an adaptable and varied behavior base. In this paper, we present a method for capturing, or learning, sequential tasks by transferring serial behavior execution from deliberative to routine control. The incorporation of this approach leads to the natural development of complex and varied behaviors, with lower demands for planning, coordination and resources. We demonstrate how this process can be performed autonomously as part of the normal function of the robot, without the need for an explicit learning stage or user guidance. The complete implementation of this algorithm on the Sony QRIO humanoid robot is described.

Key Words: action selection • developmental robotics • routine behavior • humanoid robot • robot architecture

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