Incorporating Reactive Learning Behaviour into a Mini-robot Platform

In this paper we propose an approach to robot learning by imitation that uses the multimodal inputs of language instruction, vision and motor. In our approach a student robot learns from a teacher robot how to perform three separate behaviours, 'pick', 'lift' and 'go' based on these inputs. We considered two neural architectures for performing this robot learning. First, a one-step architecture trained with two different learning approaches either based on Kohonen's self-organising map or based on the Helmholtz machine turns out to be inefficient or not capable of performing differentiated behaviour. In response we produced a hierarchical architecture that combines both learning approaches to overcome these problems. In doing o the proposed robot system models specific aspects of learning using concepts of the mirror neuron system and the hierarchical organisation of the motor system with regards to demonstration learning.

@InProceedings{ELW03, 
 	 author =  {Elshaw, Mark I. and Lewis, Debra and Wermter, Stefan},  
 	 title = {Incorporating Reactive Learning Behaviour into a Mini-robot Platform}, 
 	 booktitle = {Proceedings of the The Twenty-third SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence},
 	 editors = {Ellis, Richard; Macintosh, Ann},
 	 number = {},
 	 volume = {},
 	 pages = {255--266},
 	 year = {2003},
 	 month = {Dec},
 	 publisher = {},
 	 doi = {10.1007/978-0-85729-412-8_19}, 
 }