DocumentCode :
2506876
Title :
Bio-mimetic machine learning based on compound control
Author :
Shimoda, Shingo ; Kimura, Hidenori
Author_Institution :
BSI-Toyota Collaboration Center, RIKEN, Wako
fYear :
2008
fDate :
19-22 Oct. 2008
Firstpage :
144
Lastpage :
151
Abstract :
Tacit learning is a new machine learning paradigm that attempts to implement the superb adaptation capability of living organisms to unexpected environmental changes. It emphasizes body/environment interactions and is equipped with some elementary sets of action rules and appropriate initial conditions of the neural states that correspond to elementary survival reflexes. Along this line, we propose a new scheme of neural computation based on compound control which represents a typical feature of biological controls. This scheme is based on a classical neuron model where macroscopic purposeful behavior emerges as the result of the interaction of local rules. This scheme is applied to a bipedal robot and generates the rhythm of walking without any model of robot dynamics and environments.
Keywords :
biomimetics; gait analysis; humanoid robots; learning (artificial intelligence); legged locomotion; neural nets; robot dynamics; biomimetic machine learning; bipedal robot; body-environment interaction; classical neuron model; compound control; elementary survival reflex; environmental changes; neural computation; robot dynamics; tacit learning; walking; Biological control systems; Biological system modeling; Biology computing; Evolution (biology); Legged locomotion; Machine learning; Motor drives; Neurons; Organisms; Robot control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Robotics and Biomechatronics, 2008. BioRob 2008. 2nd IEEE RAS & EMBS International Conference on
Conference_Location :
Scottsdale, AZ
Print_ISBN :
978-1-4244-2882-3
Electronic_ISBN :
978-1-4244-2883-0
Type :
conf
DOI :
10.1109/BIOROB.2008.4762828
Filename :
4762828
Link To Document :
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