In this paper we present a first order classical metatheory, called MT, with the following properties: (1) tactics are terms of the language of MT (we call these tactics, Logic Tactics); (2) there exists a mapping between Logic Tactics and the tactics developed as programs within the GETFOL theorem prover (we call these tactics, Program Tactics). MT is expressive enough to represent the most interesting tacticals, i.e. then, orelse, try, progress and repeat. repeat allows us to express Logic Tactics which correspond to Program Tactics which may not terminate. This work is part of a larger project which aims at the development and mechanization of a metatheory which can be used to reason about, extend and, possibly, modify the code implementing Program Tactics and the GETFOL basic inference rules.

We describe a meta-logic for characterizing the evolving internal reasoning of various families of agents. We view the reasoning of agents as ongoing processes rather than as fixed sets of conclusions. Our approach utilizes a strongly sorted calculus, distinguishing the application language, time, and various syntactic sorts. We have established soundness and completeness results corresponding to various families of agents. This allows for useful and intuitively natural characterizations of such agents' reasoning abilities. We discuss and contrast consistency issues as in the work of Montague and Thomason. We also show how to represent the concept of focus of attention in this framework. This material is based upon work supported by the National Science Foundation under Grant No. IIS9907482. We wish to thank the referees for their valuable comments and suggestions. 1 Keywords: logics of knowledge and beliefs, bounded agents, real-time reasoning, multiple agents. 1 Introduct...

This paper describes a reasoning system, called GETFOL, able to introspect (the code implementing) its own deductive machinery, to reason deductively about it in a declarative metatheory and to produce new executable code which can then be pushed back into the underlying implementation. In this paper we discuss the general architecture of GETFOL and the problems related to its implementation.

We propose a framework, called OM pairs, for the formalization of metareasoning. OM pairs allow us to generate deductively the object theory and/or the meta theory. This is done by imposing, via appropriate reflection rules, the relation we want to hold between the object theory and the meta theory. In this paper we concentrate on the proof theory of OM pairs. We study them from three different points of view: we compare the strength of the object and meta theories generated by different OM pairs; for each OM pair we study the precise form of the object theory and meta theory; and, finally, we study three important case studies.

In the last decade the concept of context has been extensively exploited in many research areas, e.g., distributed artificial intelligence, multi agent systems, distributed databases, information integration, cognitive science, and epistemology. Three alternative approaches to the formalization of the notion of context have been proposed: Giunchiglia and Serafini's Multi Language Systems (ML systems), McCarthy's modal logics of contexts, and Gabbay's Labelled Deductive Systems. Previous papers have argued in favor of ML systems with respect to the other approaches. Our aim in this paper is to support these arguments from a theoretical perspective. We provide a very general definition of ML systems, which covers all the ML systems used in the literature, and we develop a proof theory for an important subclass of them: the MR systems. We prove various important results; among other things, we prove a normal form theorem, the sub-formula property, and the decidability of an important instance of the class of the MR systems. The paper concludes with a detailed comparison among the alternative approaches.

We present the basic principles and possible applications of systems capable of meta-reasoning and reflection. After a discussion of the seminal approaches, we outline our own perception of the state of the art, mainly but not only in computational logic and logic programming. We review relevat successful...

We propose multi-context systems (MC systems) as a formal framework for the specification of complex reasoning. MC systems provide the ability to structure the specification of "global" reasoning in terms of "local" reasoning sub-patterns. Each sub-pattern is modeled as a deduction in a context, formally defined as an axiomatic formal system. The global reasoning pattern is modeled as a concatenation of contextual deductions via bridge rules, i.e. inference rules that infer a fact in one context from facts asserted in other contexts. Besides the formal framework, in this paper we propose a three layer architecture designed to specify and automatize complex reasoning. At the first level we have object-level contexts (called s-contexts) for domain specifications. Problem solving principles and, more in general, meta-level knowledge about the application domain is specified in a distinct context, called Problem Solving Context (PSC). On top of s-contexts and PSC, we have a further context, called MT , where it is possible to specify strategies to control multi-context reasoning spanning through s-contexts and PSC. We show how GETFOL can be used as a computer tool for the implementation of MC systems and for the automatization of multi-context deductions.

Flexible problem solving consists of the dynamic selection and configuration of problem solving methods for a particular problem type, depending on the particular problem and the goal of problem solving. In this paper, we propose an architecture that supports such flexible problem solving automatically. For this purpose, problem solving methods are described in a uniform way, by an abstract model of components, which together define the functionality of the methods. Such an abstract model is used for dynamic selection and configuration of the problem solving methods. The proposed architecture for flexible problem solving consists of well known reflection techniques: two object-meta relations, a definable naming mechanism and the axiomhood and theoremhood reflection rules. We have succeeded in using standard meta-architecture techniques to enable flexible problem solving. 1 Introduction The literature on Knowledge Engineering of the past decade has identified a number of different probl...

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The expressivity of rewriting logic as meta-logic has been already convincingly illustrated. The goal of this paper is to explore the reflective capabilities of ELAN, a language based on the concepts of computational systems and rewriting logic. We define a universal theory for the class of ELAN programs and the representation function associated to this universal theory. Then we detail the effective transformations to implement and propose the definition of two built-in modules that provide the last step to get the reflective capabilities we want for the ELAN system. 1