Super Logic Programs

The Autoepistemic Logic of Knowledge and Belief (AELB) is a powerful nonmonotic formalism introduced by Teodor Przymusinski in 1994. In this paper, we specialize it to a class of theories called `super logic programs'. We argue that these programs form a natural generalization of standard logic programs. In particular, they allow disjunctions and default negation of arbibrary positive objective formulas. Our main results are two new and powerful characterizations of the static semant ics of these programs, one syntactic, and one model-theoretic. The syntactic fixed point characterization is much simpler than the fixed point construction of the static semantics for arbitrary AELB theories. The model-theoretic characterization via Kripke models allows one to construct finite representations of the inherently infinite static expansions. Both characterizations can be used as the basis of algorithms for query answering under the static semantics. We describe a query-answering interpreter for super programs which we developed based on the model-theoretic characterization and which is available on the web.Comment: 47 pages, revised version of the paper submitted 10/200

Transformation-Based Bottom-Up Computation of the Well-Founded Model

We present a framework for expressing bottom-up algorithms to compute the well-founded model of non-disjunctive logic programs. Our method is based on the notion of conditional facts and elementary program transformations studied by Brass and Dix for disjunctive programs. However, even if we restrict their framework to nondisjunctive programs, their residual program can grow to exponential size, whereas for function-free programs our program remainder is always polynomial in the size of the extensional database (EDB). We show that particular orderings of our transformations (we call them strategies) correspond to well-known computational methods like the alternating fixpoint approach, the well-founded magic sets method and the magic alternating fixpoint procedure. However, due to the confluence of our calculi, we come up with computations of the well-founded model that are provably better than these methods. In contrast to other approaches, our transformation method treats magic set transformed programs correctly, i.e. it always computes a relevant part of the well-founded model of the original program.Comment: 43 pages, 3 figure

IMPACTing SHOP: Foundations for integrating HTN Planning and Multi-Agency

In this paper we describe a formalism for integrating the SHOP HTN planning system with the IMPACT multi-agent environment. Our formalism provides an agentized adaptation of the SHOP planning algorithm that takes advantage of IMPACT's capabilities for interacting with external agents, performing mixed symbolic/numeric computations, and making queries to distributed, heterogeneous information sources (such as arbitrary legacy and/or specialized data structures or external databases). We show that this agentized version of SHOP will preserve soundness and completeness if certain conditions are met. (This technical report is the updated version of CS-TR-4085) (Also cross-referenced as UMIACS-TR-2000-02

A General Theory of Confluent rewriting Systems for Logic Programming and its Applications

Recently, Brass and Dix showed (\emph{Journal of Automated Reasoning} \textbf{20(1)}, 1998) that the wellfounded semantics WFS can be defined as a confluent calculus of transformation rules. This lead not only to a simple extension to disjunctive programs (\emph{Journal of Logic Programming} \textbf{38(3)}, 1999), but also to a new computation of the wellfounded semantics which is \emph{linear} for a broad class of programs. We take this approach as a starting point and generalize it considerably by developing a general theory of \emph{Confluent LP-Systems} \cfs. Such a system \cfs is a rewriting system on the set of all logic programs over a fixed signature \Lang and it induces in a natural way a canonical semantics. Moreover, we show four important applications of this theory: \emph{(1) most of the well-known semantics are induced by confluent LP-systems}, \emph{(2) there are many more transformation rules that lead to confluent LP-systems}, \emph{(3) semantics induced by such systems can be used to model aggregation}, \emph{(4) the new systems can be used to construct interesting counterexamples to some conjectures about the space of well-behaved semantics}. Also cross-referenced as UMIACS-TR-99-4

Impact: a multi-agent framework with declarative semantics

The IMPACT project (http://www.cs.umd.edu/projects/impact) aims at developing a powerful multi-agent system platform, which (1) is able to deal with heterogenous and distributed data, (2) can be realised on top of arbitrary legacy code, (3) is built on a clear foundational basis, and (4) scales up for realistic applications. We will describe its main features and several extensions of the language that have been investigated (and partially implemented

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis. © 2010 Nature America, Inc. All rights reserved.0SCOPUS: ar.jinfo:eu-repo/semantics/publishe