Ron Sun's research and system CLARION mixed neural networks for reactive control and symbolic primitives for deliberative control with a mathematical treatment nearly isomorphic to fuzzy sets and Bayesian belief networks in the control laws. He didn't do much in the literature that I'm familiar with regarding symbolic expressions for a-priori distributions, but it seems like an easy augmentation.
-----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Robert Dodier Sent: Sunday, June 04, 2006 7:58 PM To: uai@engr.orst.edu Subject: [UAI] Current status of mixed symbolic / numeric belief netinference ? Hello, I wonder if someone can comment on the status of inference in belief networks in which some probabilities have numerical values while others have symbolic values, or values given by symbolic expressions. I am aware of some work to allow conditional distributions in discrete or discrete + Gaussian to be symbolic as well as numerical. I recently did a web search and searched the UAI mailing list archives but came up empty handed. My own interest in this is to construct belief networks in which conditional distributions can be specified by name or by an expression telling the pdf or cdf, and for which some parameters might be specified by symbols or symbolic expressions. Then posterior distributions, in general, can also be symbolic expressions. The idea here is to compute posterior distributions via a computer algebra system (by formulating and evaluating integrals as needed). For well-known classes of distributions, there are much more efficient solutions. I'm looking for greater generality, at the expense of efficiency. Any comments will be much appreciated. best, Robert Dodier _______________________________________________ uai mailing list uai@ENGR.ORST.EDU https://secure.engr.oregonstate.edu/mailman/listinfo/uai _______________________________________________ uai mailing list uai@ENGR.ORST.EDU https://secure.engr.oregonstate.edu/mailman/listinfo/uai
