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15
DIPPER: Description and Formalisation of an InformationState Update Dialogue System Architecture
 In 4th SIGdial Workshop on Discourse and Dialogue
, 2003
"... The DIPPER architecture is a collection of software agents for prototyping spoken dialogue systems. Implemented on top of the Open Agent Architecture (OAA), it comprises agents for speech input and output, dialogue management, and further supporting agents. We define a formal syntax and semantics fo ..."
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Cited by 48 (16 self)
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The DIPPER architecture is a collection of software agents for prototyping spoken dialogue systems. Implemented on top of the Open Agent Architecture (OAA), it comprises agents for speech input and output, dialogue management, and further supporting agents. We define a formal syntax and semantics for the DIPPER information state update language. The language is independent...
Ivy: A Preprocessor And Proof Checker For FirstOrder Logic
, 1999
"... This case study shows how nonACL2 programs can be combined with ACL2 functions in such a way that useful properties can be proved about the composite programs. Nothing is proved about the nonACL2 programs. Instead, the results of the nonACL2 programs are checked at run time by ACL2 functions, and ..."
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Cited by 29 (10 self)
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This case study shows how nonACL2 programs can be combined with ACL2 functions in such a way that useful properties can be proved about the composite programs. Nothing is proved about the nonACL2 programs. Instead, the results of the nonACL2 programs are checked at run time by ACL2 functions, and properties of these checker functions are proved. The application is resolution/paramodulation automated theorem proving for firstorder logic. The top ACL2 function takes a conjecture, preprocesses the conjecture, and calls a nonACL2 program to search for a proof or countermodel. If the nonACL2 program succeeds, ACL2 functions check the proof or countermodel. The top ACL2 function is proved sound with respect to finite interpretations. Introduction Our ACL2 project arose from a different kind of automated theorem proving. We work with fully automatic resolution/paramodulation theo This work was supported by the Mathematical, Information, and Computational Sciences Division subprogram...
Interpreting Definites using Model Generation
, 2000
"... We argue that model generation programs, i.e., deduction systems that automatically compute the models satisfying a given finite set of formulas, can provide a procedural interpretation for semantic theories of natural language. We illustrate this claim by describing how singular definite descriptio ..."
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Cited by 16 (0 self)
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We argue that model generation programs, i.e., deduction systems that automatically compute the models satisfying a given finite set of formulas, can provide a procedural interpretation for semantic theories of natural language. We illustrate this claim by describing how singular definite descriptions can be interpreted using the higherorder model generator KIMBA.
Talking to Godot: Dialogue with a Mobile Robot
 In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2002
, 2002
"... Godot is a mobile robot platform that serves as a testbed for the interface between a sophisticated lowlevel robot navigation and a symbolic highlevel spoken dialogue system. The interesting feature of this combined system is that information flows in two directions: (1) The navigation system suppl ..."
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Cited by 15 (2 self)
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Godot is a mobile robot platform that serves as a testbed for the interface between a sophisticated lowlevel robot navigation and a symbolic highlevel spoken dialogue system. The interesting feature of this combined system is that information flows in two directions: (1) The navigation system supplies landmark information from the cognitive map used for the interpretation of the user's utterances in the dialogue system. (2) The semantic content of utterances analysed by the dialogue system are used to adjust probabilities about the robot's position in the navigation system.
Solving logic puzzles: From robust processing to precise semantics
 In Proc. of 2nd Workshop on Text Meaning and Interpretation, ACL04
, 2004
"... This paper presents intial work on a system that bridges from robust, broadcoverage natural language processing to precise semantics and automated reasoning, focusing on solving logic puzzles drawn from sources such as the Law School Admission Test (LSAT) and the analytic section of the Graduate Re ..."
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Cited by 14 (2 self)
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This paper presents intial work on a system that bridges from robust, broadcoverage natural language processing to precise semantics and automated reasoning, focusing on solving logic puzzles drawn from sources such as the Law School Admission Test (LSAT) and the analytic section of the Graduate Record Exam (GRE). We highlight key challenges, and discuss the representations and performance of the prototype system.
Implementing the binding and accommodation theory for anaphora resolution and presupposition projection
 COMPUTATIONAL LINGUISTICS
, 2003
"... ... this article. BAT is reformulated to meet requirements for computational implementation, which include operations on discourse representation structures (renaming and merging), the representation of presuppositions (allowing for selective binding and determining free and bound variables), and a ..."
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Cited by 12 (6 self)
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... this article. BAT is reformulated to meet requirements for computational implementation, which include operations on discourse representation structures (renaming and merging), the representation of presuppositions (allowing for selective binding and determining free and bound variables), and a formulation of the acceptability constraints imposed by BAT. An efficient presupposition resolution algorithm is presented, and several further improvements such as preferences for binding and accommodation are discussed and integrated in this algorithm. Finally, innovative use of firstorder theorem provers to carry out consistency checking of discourse representations is investigated.
Model Building for Natural Language Understanding
 in: Proceedings of ICoS4
, 2001
"... Contents 1 Introduction 1 2 Model Building 3 2.1 FirstOrder Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Constructing Models for Logical Theories . . . . . . . . . . . . . . . . . . . . . . . 4 2.3 Inconsistent Theories . . . . . . . . . . . . . . . . . . . . ..."
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Cited by 7 (0 self)
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Contents 1 Introduction 1 2 Model Building 3 2.1 FirstOrder Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Constructing Models for Logical Theories . . . . . . . . . . . . . . . . . . . . . . . 4 2.3 Inconsistent Theories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3 Linguistic Applications 5 3.1 Information Seeking Dialogue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.2 Controlling a Mobile Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.3 Question Answering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 4 Using Inference Tools 8 4.1 Automated Model Builders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 4.2 Automated Theorem Provers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 4.3 System Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10<F18.67
Finite Model Building: Improvements and Comparisons
 In: Model Computation – Principles, Algorithms, Applications, CADE19 Workshop W4
, 2003
"... The paper ivestigates nite model building for rst order logic. We consider two main categories of methods: Macetype and Falcontype methods. The paper has two goals: rst, presenting several improvements and strategies for the basic Macetype and Falcontype algorithms, second, comparing the e ..."
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Cited by 5 (0 self)
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The paper ivestigates nite model building for rst order logic. We consider two main categories of methods: Macetype and Falcontype methods. The paper has two goals: rst, presenting several improvements and strategies for the basic Macetype and Falcontype algorithms, second, comparing the eciency of dierent methods. The improvements to the Macetype algorithms are focused on decreasing the size of the propositional subtasks. A new cell selection heuristics is introduced for the Falcontype algorithms. The methods are implemented in the Gandalf theorem prover. We present both the eect of the introduced improvements and the comparison of method categories for several problem classes, based on their syntactical characteristics. Finally, several suggestions for further investigations are given.
Definites and the Proper Treatment of Rabbits
 in Proceedings of Inference in Computational Semantics, eds., Christof Monz and Maarten de Rijke
, 1999
"... We argue that model generation programs, i.e., deduction systems that automatically compute the interpretations satisfying a given formula, can provide a procedural interpretation for semantic theories of natural language. We illustrate this claim by describing how the higherorder model generat ..."
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Cited by 4 (1 self)
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We argue that model generation programs, i.e., deduction systems that automatically compute the interpretations satisfying a given formula, can provide a procedural interpretation for semantic theories of natural language. We illustrate this claim by describing how the higherorder model generator Kimba interprets definite descriptions. 1 Introduction The concept of a Discourse Model has repeatedly been advocated as an essential component of natural language understanding. In cognitive psychology, discourse models have been used to explain inferences that people draw in understanding text [3]. In artificial intelligence, Webber proposes them as describing the situation/state which the speaker is talking about [21]. The understanding task then consists in an attempt by the listener to synthesize the appropriate discourse model. In the dynamic/DRT (Discourse Representation Theory [10]) trend of natural language semantics, it represents the context created by previous discourse and ...
Application of model search to lattice theory
 AAA Newsletter
, 2001
"... We have used the firstorder modelsearching programs MACE and SEM to study various problems in lattice theory. First, we present a case study in which the two programs are used to examine the differences between the stages along the way from lattice theory to Boolean algebra. Second, we answer seve ..."
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Cited by 2 (0 self)
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We have used the firstorder modelsearching programs MACE and SEM to study various problems in lattice theory. First, we present a case study in which the two programs are used to examine the differences between the stages along the way from lattice theory to Boolean algebra. Second, we answer several questions posed by Norman Megill and Mladen Pavičić on