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arXiv · 1302.3571

Some Experiments with Real-Time Decision Algorithms

Bruce D'Ambrosio·Scott Burgess
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Abstract

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], PK-reduced. We discuss the implications of these experimental results and explore the broader applicability of these algorithms.

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Bruce D'Ambrosio, Scott Burgess. 2013-02-13. Some Experiments with Real-Time Decision Algorithms. https://arxiv.org/abs/1302.3571

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