TAILIEUCHUNG - Báo cáo khoa học: "REPRESENTING KNOWLEDGE ABOUT KNOWLEDGE AND MUTUAL KNOWLEDGE"

In order to represent speech acts, in a multi-agent context, we choose a knowledge representation based on the modal logic of knowledge KT4 which is defined by Sato. Such a formalism allows us to reason about knowledge and represent knowledge about knowledge, the notions of truth value and of definite reference. | REPRESENTING KNOWLEDGE ABOUT KNOWLEDGE AND MUTUAL KNOWLEDGE Said Soulhi Equipe de Comprehension du Raisonnement Naturel LSI - UPS 118 route de Narbonne 31062 Toulouse - FRANCE ABSTRACT In order to represent speech acts in a multi-agent context we choose a knowledge representation based on the modal logic of knowledge KT4 which is defined by Sato. Such a formalism allows US to reason about knowledge and represent knowledge about knowledge the notions of truth value and of definite reference. I INTRODUCTION Speech act representation and the language planning require that the system can reason about intensional concepts like knowledge and belief. A problem resolver must understand the concept of knowledge and know for example what knowledge it needs to achieve specific goals. Our assumption is that a theory of language is part of a theory of action Austin 14 . Reasoning about knowledge encounters the problem of intensionality. One aspect of this problem is the indirect reference introduced by Frege 7 during the last century. Me earthy ỊÌ5J presents this problem by giving the following example Let the two phrases Pat knows Mike s telephone number 1 and Pat dialled Mike s telephone number 2 The meaning of the proposition Mike s telephone number in 1 is the concept of the telephone number whereas its meaning in 2 is the number itself. Then if we have Mary s telephone number Mike s telephone number we can deduce that Pat dialled Mary s telephone number but we cannot deduce that Pat knows Mary s telephone number because Pat may not have known the equality mentioned above. Thus there are verbs like to know to believe and to want that create an opaque context. For Frege a sentence is a name refe rence of a sentence is its truth value the sense of a sentence is the proposition. In an oblique context the reference becomes the proposition. For example the referent of the sentence p in the indirect context A knows that p is a proposition and no longer a truth value. Me Carthy 15

• Báo cáo khoa học
• REPRESENTING KNOWLEDGE ABOUT KNOWLEDGE
• Sald Soulhi
• MUTUAL KNOWLEDGE
• scientific reports
• model language
• process natural language
• Dialog Control
• Natural Language System
• Dialog Control in a Natural Language System
• Expanding the Horizons
• Natural Language Interfaces
• Phil Hayes
• PROSPECTS OR PRACTICAL
• NATURAL LANGUAGE SYSTEMS
• Workshops
• NATURAL LANGUAGE
• INTERACTION WITH MACHINES
• Long Papers
• COMPUTER INTEBFACE DESIGN MURRAY TUROFF DEPARTMENT OF COMPUTER
• IiVFORMATION SCIENCE IIEW JERSEY INSTITUTE OF TECHNOLOGY
• EVALUATION OF NATURAL LANGUAGE
• INTERFACES TO DATABASE SYSTEMS
• A PANEL DISCUSSION
• database query system
• J
• Norwood Crout
• INTERFACES TO DATA BASE SYSTEMS
• Bozena Henisz
• INTERPRETING NATURAL LANGUAGE
• DATABASE UPDATES
• S
• Jermld Kaplan Jim David
• TRANSPORTABLE NATURAL LANGUAGE
• INTERFACES TO DATABASES
• Gary G
• Hendrlx and William H
• Lewis
• DATABASES THEORETICAL
• TECHNICAL ISSUES
• TRANSPORTABLE NATURAL LANGUAGE INTERFACES
• PROBLEMS AND TECHNIQUES
• Barbara J
• Grosz
• THEORETICAL TECHNICAL ISSUES
• NATURAL LANGUAGE ACCESS TO DATABASES
• R
• Petrick
• Domain Independent
• Database Access Systems
• ISSUES IN NATURAL LANGUAGE
• ACCESS TO DATABASES
• A LOGIC PROGRAMMING PERSPECTIVE
• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
• EXPRESSIONS REFERRING
• Douglas E
• Appelt
• THE TEXT SYSTEM
• NATURAL LANGUAGE GENERATION
• Kathleen R
• M
• MENTING A DATABASE
• KNOWLEDGE REPRESENTATION
• THE KEY TO THE SELECTION PROBLEM
• E
• Jeffrey Conklin David D
• McDonald
• A KNOWLEDGE ENGINEERING
• NATURAL LANGUAGE UNDERSTANDING
• Stuart C
• Shapiro
• NATURAL LANGUAGE TEXTS
• NECESSARILY GRAMMATICAL
• EVEN COMPLETE
• UNGRAMHATICALITY
• EXTRA GRAMMATICALITY
• NATURAL LANGUAGE UNDERSTANDING SYSTEMS
• Taxonomy
• Descriptions
• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln