DocumentCode :
1136956
Title :
Experience-Based Decision Making: A Satisficing Decision Tree Approach
Author :
Hüllermeier, Eyke
Author_Institution :
Dept. of Math. & Comput. Sci., Univ. of Marburg, Germany
Volume :
35
Issue :
5
fYear :
2005
Firstpage :
641
Lastpage :
653
Abstract :
This paper introduces a framework of experienced-based decision making as an extension of case-based decision making, a recently proposed alternative to expected utility theory. In experienced-based decision making, an agent faced with a new decision problem acts on the basis of experience gathered from previous problems in the past, either through predicting the utility of potential actions or through establishing a direct relationship between decision problems and appropriate actions. In the paper, a realization of the latter approach in the form of “satisficing” decision trees is proposed.
Keywords :
case-based reasoning; decision making; decision trees; utility theory; case based decision making; decision tree; experience based decision making; utility theory; Decision making; Decision theory; Decision trees; Helium; Humans; Logic; Machine learning; Problem-solving; Uncertainty; Utility theory; Bounded rationality; case-based reasoning; compilation; decision making; decision trees; machine learning;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
Publisher :
ieee
ISSN :
1083-4427
Type :
jour
DOI :
10.1109/TSMCA.2005.851145
Filename :
1495607
Link To Document :
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