Probabilistic knowledge bases

We define a new fixpoint semantics for rule based reasoning in the presence of weighted information. The semantics is illustrated on a real world application requiring such reasoning. Optimizations and approximations of the semantics are shown so as to make the semantics amenable to very large scale real world applications. We finally prove that the semantics is probabilistic and reduces to the usual fixpoint semantics of stratified Datalog if all information is certain. We implemented various knowledge discovery systems which automatically generate such probabilistic decision rules. In collaboration with a bank in Hong Kong we use one such system to forecast currency exchange rates. >

[1]  J. W. Lloyd,et al.  Foundations of logic programming; (2nd extended ed.) , 1987 .

[2]  Werner Kießling,et al.  New direction for uncertainty reasoning in deductive databases , 1991, SIGMOD '91.

[3]  David Heckerman,et al.  Probabilistic Interpretation for MYCIN's Certainty Factors , 1990, UAI.

[4]  V. S. Subrahmanian,et al.  Stable Semantics for Probabilistic Deductive Databases , 1994, Inf. Comput..

[5]  Peter Schäuble,et al.  On the expressive power of query languages , 1994, TOIS.

[6]  Michael Luby,et al.  Approximating Probabilistic Inference in Bayesian Belief Networks is NP-Hard , 1993, Artif. Intell..

[7]  Michael Kifer,et al.  On the Semantics of Rule-Based Expert Systems with Uncertainty , 1988, ICDT.

[8]  V. S. Subrahmanian,et al.  On the Expressive Power of Annotated Logic Programs , 1989, NACLP.

[9]  Adrian Walker,et al.  Towards a Theory of Declarative Knowledge , 1988, Foundations of Deductive Databases and Logic Programming..

[10]  V. S. Subrahmanian,et al.  Relating Dempster-Shafer Theory to Stable Semantics , 1991, ISLP.

[11]  Ehud Y. Shapiro,et al.  Logic Programs With Uncertainties: A Tool for Implementing Rule-Based Systems , 1983, IJCAI.

[12]  Nils J. Nilsson,et al.  Probabilistic Logic * , 2022 .

[13]  Norbert Fuhr,et al.  A Probabilistic Framework for Vague Queries and Imprecise Information in Databases , 1990, VLDB.

[14]  Fahiem Bacchus,et al.  Representing and reasoning with probabilistic knowledge - a logical approach to probabilities , 1991 .

[15]  Franz Baader.  A Formal Definition for the Expressive Power of Knowledge Representation Languages , 1990, ECAI.

[16]  Emanuel Parzen,et al.  Modern Probability Theory And Its Applications , 1962 .

[17]  M. H. van Emden,et al.  Quantitative Deduction and its Fixpoint Theory , 1986, J. Log. Program..

[18]  Robert A. Kowalski,et al.  The Semantics of Predicate Logic as a Programming Language , 1976, JACM.

[19]  V. S. Subrahmanian,et al.  Probabilistic Logic Programming , 1992, Inf. Comput..

[20]  Judea Pearl,et al.  Probabilistic Semantics for Nonmonotonic Reasoning: A Survey , 1989, KR.

[21]  Ashok K. Chandra.  Theory of database queries , 1988, PODS '88.

[22]  Beat Wuthrich,et al.  Knowledge discovery in databases , 1996 .

[23]  Hector Garcia-Molina,et al.  A Probalilistic Relational Data Model , 1990, EDBT.

[24]  Saso Dzeroski,et al.  Inductive Learning in Deductive Databases , 1993, IEEE Trans. Knowl. Data Eng..

[25]  Beat Wüthrich.  Towards Probabilistic Knowledge Bases , 1992, LPAR.