@inproceedings{703894c848b349c4aaebf90580ebff97,
title = "Belief revision and possibilistic logic for adaptive information filtering agents",
abstract = "Prototypes of adaptive information agents have been developed to alleviate the problem of information overload on the Internet. However, the explanatory power and the learning autonomy of these agents are weak. A logic based framework for the development of information agents is appealing since semantic relationships among information objects can be captured and reasoned about. This sheds light on better explanatory power and higher learning autonomy of information agents. The paper illustrates how the AGM belief revision and possibilistic logic can be applied to develop the learning and the filtering components of adaptive information filtering agents. Their impact on the agents' learning autonomy and explanatory power is also discussed.",
keywords = "Adaptive filters, Art, Australia, Computational Intelligence Society, Feedback, Information filtering, Information filters, Information retrieval, Internet, Logic",
author = "R. Lau and {Ter Hofstede}, {A. H M} and Bruza, {P. D.} and Wong, {K. F.}",
year = "2000",
doi = "10.1109/TAI.2000.889841",
language = "English",
isbn = "769509096",
volume = "2000-January",
publisher = "IEEE Computer Society",
pages = "19--26",
booktitle = "Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI",
address = "United States",
note = "12th IEEE Internationals Conference on Tools with Artificial Intelligence, ICTAI 2000 ; Conference date: 13-11-2000 Through 15-11-2000",
}