Some Experiments with Real-time Decision Algorithms

نویسندگان

  • Bruce D'Ambrosio
  • Scott Burgess
چکیده

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.

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تاریخ انتشار 1996