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12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00)
Belief revision and possibilistic logic for adaptive information filtering agents
Vancouver, British Columbia, Canada
November 13-November 15
ISBN: 0-7695-0909-6
ASCII Text
x 
 
R. Lau, A.H.M. ter Hofstede, P.D. Bruza, K.F. Wong, "Belief revision and possibilistic logic for adaptive information filtering agents," Tools with Artificial Intelligence, IEEE International Conference on, pp. 0019, 12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00), 2000.
 
 
BibTex
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@article{ 10.1109/TAI.2000.889841,
author = {R. Lau and A.H.M. ter Hofstede and P.D. Bruza and K.F. Wong},
title = {Belief revision and possibilistic logic for adaptive information filtering agents},
journal ={Tools with Artificial Intelligence, IEEE International Conference on},
volume = {0},
year = {2000},
isbn = {0-7695-0909-6},
pages = {0019},
doi = {http://doi.ieeecomputersociety.org/10.1109/TAI.2000.889841},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Tools with Artificial Intelligence, IEEE International Conference on
TI - Belief revision and possibilistic logic for adaptive information filtering agents
SN - 0-7695-0909-6
SP
EP
A1 - R. Lau,
A1 - A.H.M. ter Hofstede,
A1 - P.D. Bruza,
A1 - K.F. Wong,
PY - 2000
KW - belief maintenance; possibility theory; adaptive systems; software agents; learning (artificial intelligence); information retrieval; belief revision; possibilistic logic; adaptive information filtering agents; adaptive information agents; information overload; Internet; explanatory power; learning autonomy; logic based framework; information agents; semantic relationships; information objects; AGM belief revision; filtering components
VL - 0
JA - Tools with Artificial Intelligence, IEEE International Conference on
ER -
 
R. Lau, CIS Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
A.H.M. ter Hofstede, CIS Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
P.D. Bruza, CIS Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
K.F. Wong, CIS Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
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.
Index Terms:
belief maintenance; possibility theory; adaptive systems; software agents; learning (artificial intelligence); information retrieval; belief revision; possibilistic logic; adaptive information filtering agents; adaptive information agents; information overload; Internet; explanatory power; learning autonomy; logic based framework; information agents; semantic relationships; information objects; AGM belief revision; filtering components
Citation:
R. Lau, A.H.M. ter Hofstede, P.D. Bruza, K.F. Wong, "Belief revision and possibilistic logic for adaptive information filtering agents," ictai, pp.0019, 12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00), 2000
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