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- W2058323675 abstract "Biology has been an important source of inspiration in building adaptive autonomous robotic systems. Due to the inherent complexity of these models, most biologically-inspired robotic systems tend to be ethological without linkage to underlying neural circuitry. Yet, neural mechanisms are crucial in modelling adaptation and learning. The work presented in this paper describes a schema and neural network multi-level modelling approach to biologically inspired autonomous robotic systems. A prey acquisition model with detour behaviour in frogs is presented to exemplify the modelling approach. The model is tested with simulated and physical robots using the ASL/NSL and MIRO robotic system." @default.
- W2058323675 created "2016-06-24" @default.
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- W2058323675 date "2008-02-01" @default.
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- W2058323675 title "From schemas to neural networks: A multi-level modelling approach to biologically-inspired autonomous robotic systems" @default.
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- W2058323675 doi "https://doi.org/10.1016/j.robot.2007.05.007" @default.
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