Classical propositional logic plays a prominent role in industrial applications, and yet the complexity of this logic is presumed to be non-feasible. Tractable systems such as depth-bounded boolean logics approximate ...
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Classical propositional logic plays a prominent role in industrial applications, and yet the complexity of this logic is presumed to be non-feasible. Tractable systems such as depth-bounded boolean logics approximate classical logic and can be seen as a model for resource-bounded agents whose reasoning style is nonetheless classical. In this paper we first study a hierarchy of tractable logics that is not defined by depth. Then we extend it into a modal logic where modalities make explicit the assumptions discharged in propositional proofs, thereby expressing blueprints for proofs. A natural deduction system is provided that permits to reason about and manage such proof blueprints.
This paper mainly focuses on the following two issues: the knowledge and problems representation on the Web, and how a theorem-proving system can provide users on the Web with theorem-proving Web services. As to the f...
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ISBN:
(纸本)0780378407
This paper mainly focuses on the following two issues: the knowledge and problems representation on the Web, and how a theorem-proving system can provide users on the Web with theorem-proving Web services. As to the first issue, we propose MSKML (Many-Sorted Knowledge Markup Language) as the language for knowledge and problems representation on the Web;as to the second, the theorem-proving server provides Web users with theorem-proving services through the SOAP (Simple Object Access Protocol). When a client on the Web need the theorem-proving services, it represents the problem as a XML (Extensible Markup Language) file conforming to the MSKML DTD (Document Type Definition) and sends a SOAP request message including the XML file to the theorem-proving server, and the theorem-proving server represents the solution as a XML file conforming to the MSKML DTD and send it back to the client as the SOAP response message.
This paper mainly focuses on the following two issues:the knowledge and problems representation on the Web,and how a theorem-proving system can provide users on the Web with theorem-proving Web *** to the first issue,...
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This paper mainly focuses on the following two issues:the knowledge and problems representation on the Web,and how a theorem-proving system can provide users on the Web with theorem-proving Web *** to the first issue,we propose MSKML(Many-Sorted Knowledge Markup Language) as the language for knowledge and problems representation on the Web;as to the second,the theorem-proving server provides Web users with theorem-proving services through the SOAP(Simple Object Access Protocol).When a client on the Web need the theorem-proving services,it represents the problem as a XML(Extensible Markup Language) file conforming to the MSKML DTD(Document Type Definition) and sends a SOAP request message including the XML file to the theorem-proving server,and the theorem-proving server represents the solution as a XML file conforming to the MSKML DTD and send it back to the client as the SOAP response message.
The DISCOUNT system is a distributed equational theorem prover based on the teamwork method for knowledge-based distribution. It uses an extended version of unfailing Knuth-Bendix completion that is able to deal with ...
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The DISCOUNT system is a distributed equational theorem prover based on the teamwork method for knowledge-based distribution. It uses an extended version of unfailing Knuth-Bendix completion that is able to deal with arbitrarily quantified goals. DISCOUNT features many different control strategies that cooperate using the teamwork approach. Competition between multiple strategies, combined with reactive planning, results in an adaptation of the whole system to given problems, and thus in a very high degree of independence from user interaction. Teamwork also provides a suitable framework for the use of control strategies based on learning from previous proof experiences. One of these strategies forms the core of the expert global learn, which is capable of learning from successful proofs of several problems. This expert, running sequentially, was one of the entrants in the competition (DISCOUNT/GL), while a distributed DISCOUNT system running on two workstations was another entrant.
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