Collaborating Authors

Concurrent Logic Programming, Metaprogramming, and Open Systems

AI Magazine

An informal workshop on concurrent logic programming, metaprogramming, and open systems was held at Xerox Palo Alto Research Center (PARC) on 8-9 September 1987 with support from the Association for the Advancement of Artificial Intelligence. The 50 workshop participants came from the Japanese Fifth Generation Project (ICOT), the Weizmann Institute of Sci-ence in Israel, Imperial College in London, the Swedish Institute of Computer Science, Stanford University, the Mas-sachusetts Institute of Technology (MIT), Carnegie Mellon University (CMU), Cal Tech, Science University of Tokyo, Melbourne University, Calgary University, University of Wisconsin, Case Western Reserve, University of Oregon, Korea Advanced Institute of Science and Technology (KAIST), Quintus, Symbolics, IBM, and Xerox PARC. No proceedings were generated; instead, participants distributed copies of drafts, slides, and recent papers.

The 1993 International Logic Programming Symposium

AI Magazine

The 1993 International Logic Programming Symposium was held in Vancouver, British Columbia, on 26-29 October. It presented the state of the art in logic programming, emphasizing the deliberate interaction with other fields, in particular, humanistic fields. Topics covered at the symposium included algorithmic analysis, programming methodologies, semantic analysis, deductive databases, and programming language design.

A System for Explainable Answer Set Programming Artificial Intelligence

Answer Set Programming (ASP) [13, 12, 4] is a successful paradigm for Knowledge Representation and problem solving. Under this paradigm, the programmer represents a problem as a logic program formed by a set of rules and obtains solutions to that problem in terms of models of the program called answer sets. Thanks to the availability of efficient solvers, ASP is nowadays applied in a wide variety of areas including robotics, bioinformatics, music composition [7, 5, 3], and many more. An ASP program does not contain information about the method to obtain the answer sets, something that is completely delegated to the ASP solver. This, of course, has the advantage of making ASP a fully declarative language, where the programmer must concentrate on specification rather than on design of search algorithms.

ProGS: Property Graph Shapes Language (Extended Version) Artificial Intelligence

Property graphs constitute data models for representing knowledge graphs. They allow for the convenient representation of facts, including facts about facts, represented by triples in subject or object position of other triples. Knowledge graphs such as Wikidata are created by a diversity of contributors and a range of sources leaving them prone to two types of errors. The first type of error, falsity of facts, is addressed by property graphs through the representation of provenance and validity, making triples occur as first-order objects in subject position of metadata triples. The second type of error, violation of domain constraints, has not been addressed with regard to property graphs so far. In RDF representations, this error can be addressed by shape languages such as SHACL or ShEx, which allow for checking whether graphs are valid with respect to a set of domain constraints. Borrowing ideas from the syntax and semantics definitions of SHACL, we design a shape language for property graphs, ProGS, which allows for formulating shape constraints on property graphs including their specific constructs, such as edges with identities and key-value annotations to both nodes and edges. We define a formal semantics of ProGS, investigate the resulting complexity of validating property graphs against sets of ProGS shapes, compare with corresponding results for SHACL, and implement a prototypical validator that utilizes answer set programming.

Interpolable Formulas in Equilibrium Logic and Answer Set Programming

Journal of Artificial Intelligence Research

Interpolation is an important property of classical and many non-classical logics that has been shown to have interesting applications in computer science and AI. Here we study the Interpolation Property for the the non-monotonic system of equilibrium logic, establishing weaker or stronger forms of interpolation depending on the precise interpretation of the inference relation. These results also yield a form of interpolation for ground logic programs under the answer sets semantics. For disjunctive logic programs we also study the property of uniform interpolation that is closely related to the concept of variable forgetting. The first-order version of equilibrium logic has analogous Interpolation properties whenever the collection of equilibrium models is (first-order) definable. Since this is the case for so-called safe programs and theories, it applies to the usual situations that arise in practical answer set programming.