The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Online ISSN : 2424-3124
2012
Session ID : 1A1-F06
Conference information
1A1-F06 Learning Theory Based on Behavioral Representations(Evolution and Learning for Robotics(1))
Gakuto MASUYAMAAtushi YAMASHITAHajime ASAMA
Author information
CONFERENCE PROCEEDINGS FREE ACCESS

Details
Abstract
For the purpose of designing autonomous robot that can be utilized at a social scene inhered in living environment of humans, developmental model of the robot based on internal behavior representation is presented. Framework of the model is discussed in terms of subjective interpretation of sensory-motor flow that reflects temporal interactions between behaviors of the robot and an external environment. Depending on constraints due to bodily natures and environmental characteristics, internal behavior representation is segmented in proposed framework. Alternatively, target-oriented time series would be induced by internal evaluator corresponding to emotion of living objects. The model is oriented to deal with an unsteady environment, including physical and social dynamics. In this paper, importance of equipping invariant criteria of value in such environment is advocated.
Content from these authors
© 2012 The Japan Society of Mechanical Engineers
Previous article Next article
feedback
Top