this paper, we present an equational logic framework for objects, methods, inheritance and overriding of methods. Overriding is achieved via the concept of specificity, which states that more specific methods are preferred to less specific ones. Specificity is computed with the help of negation as failure. We specify equational logic programs and show that their completed versions behave as intended. Furthermore, we prove that SLDENF-resolution is complete if the equational theory is finitary, the completed programs are consistent, and no derivation flounders or is infinite; and we give syntactic conditions which guarantee non-floundering and finiteness. Finally, we discuss how the approach can be extended to reasoning about the past in the context of incompletely specified objects or situations. It will turn out that constructive negation is needed to solve these problems

In traditional knowledge-based system development environments, the fundamental representational building blocks are mechanisms such as frames, rules, and attached procedures. The KEE system has been extended to include both a context (worlds) system and a truth maintenance system.

In this paper, we examine current approaches and the state of the art in the application of formal methods to the analysis of authentication protocols. We use Meadows' classification of analysis techniques into four types. The Type I approach models and verifies a protocol using specification languages and verification tools not specifically developed for the analysis of cryptographic protocols. In the Type II approach, a protocol designer develops expert systems to create and examine different scenarios, from which he may draw conclusions about the security of the protocols being studied. The Type III approach models the requirements of a protocol family using logics developed specifically for the analysis of knowledge and belief. Finally, the Type IV approach develops a formal model based on the algebraic term-rewriting properties of cryptographic systems. The majority of research and the most interesting results are in the Type III approach, including reasoning systems such as the B...

Applications that require real-time processing of high-volume data steams are pushing the limits of traditional data processing infrastructures. These stream-based applications include market feed processing and electronic trading on Wall Street, network and infrastructure monitoring, fraud detection, and command and control in military environments. Furthermore, as the “sea change ” caused by cheap micro-sensor technology takes hold, we expect to see everything of material significance on the planet get “sensor-tagged ” and report its state or location in real time. This sensorization of the real world will lead to a “green field ” of novel monitoring and control applications with high-volume and low-latency processing requirements. Recently, several technologies have emerged—including off-theshelf stream processing engines—specifically to address the challenges of processing high-volume, real-time data without requiring the use of custom code. At the same time, some existing software technologies, such as main memory DBMSs and rule engines, are also being “repurposed ” by marketing departments to address these applications. In this paper, we outline eight requirements that a system should meet to excel at a variety of real-time stream processing applications. Our goal is to provide high-level guidance to information technologists so that they will know what to look for when evaluating alternative stream processing solutions. As such, this paper serves a purpose comparable to the requirements papers in relational DBMSs and on-line analytical processing. We also briefly review alternative software technologies in the context of our requirements. The paper attempts to be vendor neutral, so no specific commercial products are mentioned. 1.

Abstract. In this experience paper we present a case study in using logic programming in a pervasive computing project in the healthcare domain. An expert system is used to detect healthcare activities in a pervasive hospital environment where positions of people and things are tracked. Based on detected activities an activity-driven computing infrastructure provides computational assistance to healthcare staff on mobile- and pervasive computing equipment. Assistance range from simple activities like fast log-in into the electronic patient medical record system to complex activities like signing for medicine given to specific patients. We describe the role of logic programming in the infrastructure and discuss the benefits and problems of using logic programming in a pervasive context. 1

Linear Logic is gaining momentum in computer science because it offers a unified framework and a common vocabulary for studying and analyzing different aspects of programming and computation. We focus here on models where computation is identified with proof search in the sequent system of Linear Logic. A proof normalization procedure, called "focusing", has been proposed to make the problem of proof search tractable. Correspondingly, there is a normalization procedure mapping formulae of Linear Logic into a syntactic fragment of that logic, called LinLog, and in which the focusing normalization for proofs can be most conveniently expressed. In this paper, we propose to push this compilation/normalization process further, by applying abstract interpretation and partial evaluation techniques to (focused) proofs in LinLog. These techniques provide information concerning the evolution of the computational resources (formulae) during the execution (proof construction). The practical outcome that we expect from this theoretical effort is the definition of a general tool for statically analyzing and reasoning about the runtime behavior of programs in frameworks where computations can be accounted for in terms of proof search in Linear Logic.

Linear Logic is gaining momentum in computer science because it offers a unified framework and a common vocabulary for studying and analyzing different aspects of programming and computation. We focus here on models where computation is identified with proof search in the sequent system of Linear Logic. A proof normalization procedure, called "focusing", has been proposed to make the problem of proof search tractable. Correspondingly,

We report on experiences in the design of the programming language XC. It is an extension of C++ and combines abstract data types with rule based programming. Our design decisions are validated by three application prototypes and by benchmarking XC and OPS83. The experiences raise some critique on the RETE algorithm and on C++ as a host language. However, most of the results are also applicable to other host languages that support data abstraction. XC has been designed specifically to be used in embedded real-time expert systems.

Closed Terminologies and Temporal Reasoning in Description Logic for Concept and Plan Recognition Robert Anthony Weida Description logics are knowledge representation formalisms in the tradition of frames and semantic networks, but with an emphasis on formal semantics. A terminology contains descriptions of concepts, such as university, which are automatically classified in a taxonomy via subsumption inferences. Individuals such as columbia are described in terms of those concepts. This thesis enhances the scope and utility of description logics by exploiting new completeness assumptions during problem solving and by extending the expressiveness of descriptions. First, we introduce a predictive concept recognition methodology based on a new closed terminology assumption (CTA). The terminology is dynamically partitioned by modalities (necessary, optional, and impossible) with respect to individuals as they are specified. In our interactive configuration application, a user incrementall...

This paper presents an alternative representation language, rule schema + rule body, to rule-based production systems based on an integration of rule-based and numeric computations. Rule schemata in the language are used to describe the hierarchy among factors or nodes in domain reasoning networks while rule bodies, which comprise computing rules as well as inference rules, are used to express specific evaluation methods for the factors and/or the certainty factors of the factors in their corresponding rule schemata. By representing explicitly numeric computation and inexact calculus as well as inference rules, the language supports a flexible way to process procedural knowledge and uncertainty. A linear forward chaining algorithm, LFA, and an expert system building shell, KEshell, based on the language are also described in this paper. Key words: knowledge representation, rule-based systems, linear forward chaining, knowledge engineering shells. 1 Motivations It is probably an axio...