Query Evaluation in Deductive Databases

It is desirable to answer queries posed to deductive databases by computing fixpoints because such computations are directly amenable to set-oriented fact processing. However, the classical fixpoint procedures based on bottom-up processing — the naive and semi-naive methods — are rather primitive and often inefficient. In this article, we rely on bottom-up meta-interpretation for formalizing a new fixpoint procedure that performs a different kind of reasoning: We specify a top-down query answering method, which we call the Backward Fixpoint Procedure. Then, we reconsider query evaluation methods for recursive databases. First, we show that the methods based on rewriting on the one hand, and the methods based on resolution on the other hand, implement the Backward Fixpoint Procedure. Second, we interpret the rewritings of the Alexander and Magic Set methods as specializations of the Backward Fixpoint Procedure. Finally, we argue that such a rewriting is also needed in a database context for implementing efficiently the resolution-based methods. Thus, the methods based on rewriting and the methods based on resolution implement the same top-down evaluation of the original database rules by means of auxiliary rules processed bottom-up

Towards Intelligent Databases

This article is a presentation of the objectives and techniques of deductive databases. The deductive approach to databases aims at extending with intensional definitions other database paradigms that describe applications extensionaUy. We first show how constructive specifications can be expressed with deduction rules, and how normative conditions can be defined using integrity constraints. We outline the principles of bottom-up and top-down query answering procedures and present the techniques used for integrity checking. We then argue that it is often desirable to manage with a database system not only database applications, but also specifications of system components. We present such meta-level specifications and discuss their advantages over conventional approaches

A goal-based approach to policy refinement

As the interest in using policy-based approaches for systems management grows, it is becoming increasingly important to develop methods for performing analysis and refinement of policy specifications. Although this is an area that researchers have devoted some attention to, none of the proposed solutions address the issue of deriving implementable policies from high-level goals. A key part of the solution to this problem is having the ability to identify the operations, available on the underlying system, which can achieve a given goal. This paper presents an approach by which a formal representation of a system, based on the Event Calculus, can be used in conjunction with abductive reasoning techniques to derive the sequence of operations that will allow a given system to achieve a desired goal. Additionally it outlines how this technique might be used for providing tool support and partial automation for policy refinement. Building on previous work on using formal techniques for policy analysis, the approach presented here applies a transformation of both policy and system behaviour specifications into a formal notation that is based on Event Calculus. Finally, it shows how the overall process could be used in conjunction with UML modelling and illustrates this by means of an example. 1

Human Ecology, Process Philosophy and the Global Ecological Crisis

This paper argues that human ecology, based on process philosophy and challenging scientific materialism, is required to effectively confront the global ecological crisis now facing us