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Multilanguage Hierarchical Logics (or: How We Can Do Without Modal Logics)
, 1994
"... MultiLanguage systems (ML systems) are formal systems allowing the use of multiple distinct logical languages. In this paper we introduce a class of ML systems which use a hierarchy of first order languages, each language containing names for the language below, and propose them as an alternative to ..."
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Cited by 178 (47 self)
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MultiLanguage systems (ML systems) are formal systems allowing the use of multiple distinct logical languages. In this paper we introduce a class of ML systems which use a hierarchy of first order languages, each language containing names for the language below, and propose them as an alternative to modal logics. The motivations of our proposal are technical, epistemological and implementational. From a technical point of view, we prove, among other things, that the set of theorems of the most common modal logics can be embedded (under the obvious bijective mapping between a modal and a first order language) into that of the corresponding ML systems. Moreover, we show that ML systems have properties not holding for modal logics and argue that these properties are justified by our intuitions. This claim is motivated by the study of how ML systems can be used in the representation of beliefs (more generally, propositional attitudes) and provability, two areas where modal logics have been extensively used. Finally, from an implementation point of view, we argue that ML systems resemble closely the current practice in the computer representation of propositional attitudes and metatheoretic theorem proving.
Reasoning Theories  Towards an Architecture for Open Mechanized Reasoning Systems
, 1994
"... : Our ultimate goal is to provide a framework and a methodology which will allow users, and not only system developers, to construct complex reasoning systems by composing existing modules, or to add new modules to existing systems, in a "plug and play" manner. These modules and systems might be ..."
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Cited by 47 (11 self)
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: Our ultimate goal is to provide a framework and a methodology which will allow users, and not only system developers, to construct complex reasoning systems by composing existing modules, or to add new modules to existing systems, in a "plug and play" manner. These modules and systems might be based on different logics; have different domain models; use different vocabularies and data structures; use different reasoning strategies; and have different interaction capabilities. This paper makes two main contributions towards our goal. First, it proposes a general architecture for a class of reasoning systems called Open Mechanized Reasoning Systems (OMRSs). An OMRS has three components: a reasoning theory component which is the counterpart of the logical notion of formal system, a control component which consists of a set of inference strategies, and an interaction component which provides an OMRS with the capability of interacting with other systems, including OMRSs and hum...
Multicontext Systems as a Specification Framework for Complex . . .
 Formal Specification of Complex Reasoning Systems, Ellis Horwood
, 1992
"... this paper we propose multi context systems (MC systems from now on) as a logical framework for the formal specification of complex reasoning. MC systems have been motivated and formally introduced in [6, 7]; they are also called multilanguage systems (ML systems) to emphasize the fact that they all ..."
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Cited by 18 (2 self)
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this paper we propose multi context systems (MC systems from now on) as a logical framework for the formal specification of complex reasoning. MC systems have been motivated and formally introduced in [6, 7]; they are also called multilanguage systems (ML systems) to emphasize the fact that they allow the definition of multiple languages, each language associated with a context. The general idea is to model local reasoning as deduction inside a context. A context is formally defined as an axiomatic formal system, i.e. a triple consisting of a language, a set of axioms and a set of inference rules. Interaction between contexts is formalized via bridge rules, i.e. rules whose premises and conclusion belong to different contexts. The notion of deduction in an MC system (modeling the reasoning of the whole system) is defined as the composition, via bridge rules, of the contextual deductions
A Theoretical Framework For The Conception Of Agency
 International Journal of Intelligent Systems
, 1999
"... of growing importance. We propose a new machine, called agency, which is devoted to solve complex problems by means of cooperation among agents, where each agent is able to perform inferential activities. ..."
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Cited by 12 (10 self)
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of growing importance. We propose a new machine, called agency, which is devoted to solve complex problems by means of cooperation among agents, where each agent is able to perform inferential activities.
Formal Specification of Beliefs in MultiAgent Systems
, 1997
"... . The formalization of agents attitudes, and belief in particular, has been investigated in the past by the authors of this paper, along two different but related streams. Giunchiglia and Giunchiglia investigate the properties of contexts for the formal specification of agents mutual beliefs, combin ..."
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Cited by 12 (0 self)
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. The formalization of agents attitudes, and belief in particular, has been investigated in the past by the authors of this paper, along two different but related streams. Giunchiglia and Giunchiglia investigate the properties of contexts for the formal specification of agents mutual beliefs, combining extensional specification with (finite) presentation by means of contexts. Cimatti and Serafini address the representational and implementational implications of the use of contexts for representing propositional attitudes by tackling a paradigmatic case study. The goal of this paper is to show how these two streams are actually complementary, i.e. how the methodology proposed in the former can be successfully applied to formally specify the case study discussed in the latter. In order to achieve this goal, the formal framework is extended to take into account some relevant aspects of the case study, the specification of which is then worked out in detail. 1 Introduction Much of the wor...
A Multicontext Architecture for Formalizing Complex Reasoning
 International Journal of Intelligent Systems
, 1995
"... We propose multicontext 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 subpatterns. Each subpattern is modeled as a deduction in a context, ..."
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Cited by 8 (0 self)
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We propose multicontext 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 subpatterns. Each subpattern 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 objectlevel contexts (called scontexts) for domain specifications. Problem solving principles and, more in general, metalevel knowledge about the application domain is specified in a distinct context, called Problem Solving Context (PSC). On top of scontexts and PSC, we have a further context, called MT , where it is possible to specify strategies to control multicontext reasoning spanning through scontexts and PSC. We show how GETFOL can be used as a computer tool for the implementation of MC systems and for the automatization of multicontext deductions.
Implementing Extensible Theorem Provers
 In International Conference on Theorem Proving in HigherOrder Logic: Emerging Trends, Research Report, INRIA Sophia Antipolis
, 1999
"... . The growing application of theorem proving techniques has increased the need for customized theorem provers. Powerful provers contain numerous interacting subsystems, each of which requires substantial time and expertise to build; constructing new provers from scratch is virtually prohibitive. Plu ..."
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Cited by 8 (6 self)
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. The growing application of theorem proving techniques has increased the need for customized theorem provers. Powerful provers contain numerous interacting subsystems, each of which requires substantial time and expertise to build; constructing new provers from scratch is virtually prohibitive. Plugandplay prover frameworks promise an alternative in which developers can construct provers by selecting logics, reasoning techniques, and interfaces. Realizing such frameworks cleanly requires specialized software architectures and particular language abstractions, even for frameworks supporting only simple interactions between logics. This paper explores architectural and linguistic issues in plugandplay theorem prover development. It reflects our experience creating and using such a framework to develop several versions of a research prototype theorem prover. Keywords: extensible theorem provers, plugandplay theorem provers, software architectures, software components, programming ...
Hierarchical MetaLogics for Belief and Provability: How We Can Do Without Modal Logics
, 1992
"... MultiLanguage systems (ML systems) are formal systems allowing the use of multiple distinct logical languages. In this paper we introduce a class of ML systems which use a hierarchy of metatheories, each with a first order language containing names for the language below, and propose them as an a ..."
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Cited by 3 (3 self)
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MultiLanguage systems (ML systems) are formal systems allowing the use of multiple distinct logical languages. In this paper we introduce a class of ML systems which use a hierarchy of metatheories, each with a first order language containing names for the language below, and propose them as an alternative to modal logics. The motivations of our proposal are technical and epistemological. From a technical point of view, we prove, among other things, that modal logics can be embedded in the corresponding ML systems. Moreover, we show that ML systems have properties not holding for modal logics and argue that these properties are justified by our intuitions. We motivate our claim by studying how they can be used in the representation of beliefs (more generally, propositional attitudes) and provability, two areas where modal logics have been extensively used. 1
Dealing With Expected and Unexpected Obstacles
, 1997
"... Generality and locality have been proposed as two crucial properties for systems formalizing common sense reasoning. The first is the ability of representing knowledge in a way that makes it usable in a wide class of circumstances. The second is the ability of using only a subset of the potentially ..."
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Cited by 2 (2 self)
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Generality and locality have been proposed as two crucial properties for systems formalizing common sense reasoning. The first is the ability of representing knowledge in a way that makes it usable in a wide class of circumstances. The second is the ability of using only a subset of the potentially available knowledge, namely the subset which is held to be relevant in a given circumstance. These two properties seem to be one the opposite of the other, since disregarding part of the available information (locality) may lead to a loss of generality. In this paper, we argue that this is not the case, and propose a general methodology for combining generality and locality. This methodology is essentially based on the notion of context. As a case study, we propose a formalization of the GlasgowLondonMoscow example and its mechanization in an interactive theorem prover, GETFOL.
Multicontext Systems as a Tool to Model Temporal Evolution
, 1993
"... Contexts are defined as axiomatic formal systems. More than one context can be defined, each one modeling/solving (part of) the problem. The (global) model/solution of the problem is obtained making contexts communicate via bridge rules. Bridge rules and contexts are the components of Multi Cont ..."
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Cited by 1 (1 self)
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Contexts are defined as axiomatic formal systems. More than one context can be defined, each one modeling/solving (part of) the problem. The (global) model/solution of the problem is obtained making contexts communicate via bridge rules. Bridge rules and contexts are the components of Multi Context systems. In this paper we want to study the applicability of multi contexts systems to reason about temporal evolution.