Hybrid Sequential Machines based on Neuroscience

In the past a variety of computational problems have been tackled with dierent neural network approaches. However, very little research has been done on a framework which connects neuroscienceoriented models with connectionist models and higher level symbolic processing. In this paper, we outline a framework which focuses on a hybrid integration of various neural and symbolic preference techniques in order to shed more light on how we may process higher level concepts, for instance for language processing based on concepts from neuroscience. It is a rst hybrid framework which allows a link between various levels from neuroscience, connectionist Preference Moore machines and symbolic machines.

@InProceedings{WP00, 
 	 author =  {Wermter, Stefan and Panchev, Christo},  
 	 title = {Hybrid Sequential Machines based on Neuroscience}, 
 	 booktitle = {Proceedings of the ECAI Workshop on Foundations of Connectionist Symbolic Integration},
 	 editors = {},
 	 number = {},
 	 volume = {},
 	 pages = {13--24},
 	 year = {2000},
 	 month = {Aug},
 	 publisher = {},
 	 doi = {}, 
 }