Modular Preference Moore Machines in News Mining Agents

Stefan Wermter , Garen Arevian

Proceedings of the Joint 9th International Fuzzy Systems Association World Congress and the 20th North American Fuzzy Information Processing Society International Conference, pages 1786--1792, - Jul 2001

Associated documents :

This paper focuses on Hybrid Symbolic Neural Architectures that support the task of classifying textual information in learning agents. We give an outline of these symbolic and neural preference Moore machines. Furthermore, we demonstrate how they can be used in the context of information mining and news classification. Using the Reuters newswire text data, we demonstrate how hybrid symbolic and neural machines can provide an effective foundation for learning news agents.

@InProceedings{WA01, 
 	 author =  {Wermter, Stefan and Arevian, Garen},  
 	 title = {Modular Preference Moore Machines in News Mining Agents}, 
 	 booktitle = {Proceedings of the Joint 9th International Fuzzy Systems Association World Congress and the 20th North American Fuzzy Information Processing Society International Conference},
 	 editors = {},
 	 number = {},
 	 volume = {},
 	 pages = {1786--1792},
 	 year = {2001},
 	 month = {Jul},
 	 publisher = {IEEE},
 	 doi = {}, 
 }