Deriving a Stationary Dynamic Bayesian Network from a Logic Program with Recursive Loops

Details Deriving a Stationary Dynamic Bayesian Network from a Logic Program with Recursive Loops Deriving a Stationary Dynamic Bayesian Network from a Logic Program with Recursive Loops

2005-06-27

arxiv.org/abs/cs/0506095v1

Computer Science

Artificial Intelligence

29 pages

Scientific paper

Recursive loops in a logic program present a challenging problem to the PLP framework. On the one hand, they loop forever so that the PLP backward-chaining inferences would never stop. On the other hand, they generate cyclic influences, which are disallowed in Bayesian networks. Therefore, in existing PLP approaches logic programs with recursive loops are considered to be problematic and thus are excluded. In this paper, we propose an approach that makes use of recursive loops to build a stationary dynamic Bayesian network. Our work stems from an observation that recursive loops in a logic program imply a time sequence and thus can be used to model a stationary dynamic Bayesian network without using explicit time parameters. We introduce a Bayesian knowledge base with logic clauses of the form $A \leftarrow A_1,...,A_l, true, Context, Types$, which naturally represents the knowledge that the $A_i$s have direct influences on $A$ in the context $Context$ under the type constraints $Types$. We then use the well-founded model of a logic program to define the direct influence relation and apply SLG-resolution to compute the space of random variables together with their parental connections. We introduce a novel notion of influence clauses, based on which a declarative semantics for a Bayesian knowledge base is established and algorithms for building a two-slice dynamic Bayesian network from a logic program are developed.

Affiliated with

Also associated with

No associations

Rating

Deriving a Stationary Dynamic Bayesian Network from a Logic Program with Recursive Loops does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Deriving a Stationary Dynamic Bayesian Network from a Logic Program with Recursive Loops, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Deriving a Stationary Dynamic Bayesian Network from a Logic Program with Recursive Loops will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-646185