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1996

Some Experiments with Real-time Decision Algorithms

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Some Experiments with Real-time Decision Algorithms
Real-time Decision algorithms are a class of incremental resource-bounded [Horvitz, 89] or anytime [Dean, 93] algorithms for evaluating influence diagrams. We present a test domain for real-time decision algorithms, and the results of experiments with several Real-time Decision Algorithms in this domain. The results demonstrate high performance for two algorithms, a decision-evaluation variant of Incremental Probabilisitic Inference [D'Ambrosio, 93] and a variant of an algorithm suggested by Goldszmidt, [Goldszmidt, 95], PKreduced. We discuss the implications of these experimental results and explore the broader applicability of these algorithms.
Bruce D'Ambrosio, Scott Burgess
Added 02 Nov 2010
Updated 02 Nov 2010
Type Conference
Year 1996
Where UAI
Authors Bruce D'Ambrosio, Scott Burgess
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