Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas of Computer Science. This paper aims to chart out the main developments of the field over the last ten years and to take a critical view of these developments from several perspectives: logical, epistemological, computational and suitability to application. The paper attempts to expose some of the challenges and prospects for the further development of the field.

The goal of the research described in this paper is to develop an application-independent presentation tool that automatically designs effective graphical presentations (such as bar charts, scatter plots, and connected graphs) of relational information. Two problems are raised by this goal: The codifi-cation of graphic design criteria in a form that can be used by the presentation tool, and the generation of a wide variety of designs so that the presentation tool can accommodate a wide variety of information. The approach described in this paper is based on the view that graphical presentations are sentences of graphical languages. The graphic design issues are codified as expressiveness and effectiveness criteria for graphical languages. Expressiveness criteria determine whether a graphical language can express the desired information. Effectiveness criteria determine whether a graphical language exploits the capabilities of the output medium and the human visual system. A wide variety of designs can be systematically generated by using a composition algebra that composes a small set of primitive graphical languages. Artificial intelligence techniques are used to implement a prototype presentation tool called APT (A Presentation Tool), which is based on the composition algebra and the graphic design criteria.

This paper presents an approach to temporal reasoning in which prediction is deduction but explanation is abduction. It is argued that all causal laws should be expressed in the natural form effect if cause. Any given set of laws expressed in this way can be used for both forwards projection (prediction) and backwards projection (explanation), but abduction must be used for explanation whilst deduction is used for prediction. The approach described uses a shortened form of Kowalski and Sergot's Event Calculus and incorporates the assumption that properties known to hold must have explanations in terms of events. Using abduction to implement this assumption results in a form of default persistence which correctly handles problems which have troubled other formulations. A straightforward extension to SLD resolution is described which implements the abductive approach to explanation, and which complements the well-understood deductive methods for prediction. Introduction Temporal reason...

A family of extensions of SLDNF-resolution for normal abductive programs is presented. The main difference between our approach and existing procedures is the treatment of non-ground abductive goals. A completion semantics is given and the soundness and completeness of the procedures has been proven. The research presented here, provides a simple framework of abductive procedures, in which a number of parameters can be set, in order to fit the abduction procedure to the application under consideration.

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In this paper we provide algorithms for reasoning with partitions of related logical axioms in propositional and first-order logic (FOL). We also provide a greedy algorithm that automatically decomposes a set of logical axioms into partitions. Our motivation is two-fold. First, we are concerned with how to reason e#ectively with multiple knowledge bases that have overlap in content. Second, we are concerned with improving the e#ciency of reasoning over a set of logical axioms by partitioning the set with respect to some detectable structure, and reasoning over individual partitions. Many of the reasoning procedures we present are based on the idea of passing messages between partitions. We present algorithms for reasoning using forward message-passing and using backward message-passing with partitions of logical axioms. Associated with each partition is a reasoning procedure. We characterize a class of reasoning procedures that ensures completeness and soundness of our message-passing ...

Probabilistic Horn abduction is a simple framework to combine probabilistic and logical reasoning into a coherent practical framework. The numbers can be consistently interpreted probabilistically, and all of the rules can be interpreted logically. The relationship between probabilistic Horn abduction and logic programming is at two levels. At the first level probabilistic Horn abduction is an extension of pure Prolog, that is useful for diagnosis and other evidential reasoning tasks. At another level, current logic programming implementation techniques can be used to efficiently implement probabilistic Horn abduction. This forms the basis of an "anytime" algorithm for estimating arbitrary conditional probabilities. The focus of this paper is on the implementation. Scholar, Canadian Institute for Advanced Research Logic Programming, Abduction and Probability 2 1 Introduction Probabilistic Horn Abduction [22, 21, 23] is a framework for logic-based abduction that incorporates proba...

During the development of a system, software modules can be viewed in terms of their commitments: the constraints imposed by their own structure and behavior, and by their relationships with other modules (in terms of resource consumption, data requirements, etc.). The Comet system uses explicit representation and reasoning with commitments to aid the software design and development process -- in particular, to lead software developers to make decisions that result in reuse. Developers can examine the commitments that must be met in order to include an existing module, and can explore how commitments change when modules are modified. Comet has been applied to the domain of sensor-based tracker software. I. Introduction A major problem for software developers is judging how a change in a module affects and is affected by the rest of the design. Modules need to change for a variety of reasons: an existing system is modified, a change in an ongoing design is proposed, a bug is found, et...

This paper discusses the algorithm we are using for the mediation of queries to disparate information sources in a Context Interchange system, where information sources may have di erent interpretations arising from their respective context. Queries are assumed to be formulated without regard for semantic heterogeneity, and are rewritten to corresponding mediated queries by taking into account the semantics of data codi ed in axioms associated with sources and receivers (the corresponding context theories). Our approach draws upon recent advances in abductive logic programming and presents an integration of techniques for query rewriting and semantic query optimization. We also demonstrate how thiscanbe e ciently implemented using the constraint logic programming system ECLiPSe. 1

Authoring is a complex, knowledge-intensive activity which until recently has been performed exclusively by humans. New computer-based techniques have added horsepower rather than intelligence to traditional approaches, and have not addressed their principal limitations, chief of which is the inability to tailor presentations to individual users at run-time. We believe