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...

This case study shows how non-ACL2 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 non-ACL2 programs. Instead, the results of the non-ACL2 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 first-order logic. The top ACL2 function takes a conjecture, preprocesses the conjecture, and calls a non-ACL2 program to search for a proof or countermodel. If the non-ACL2 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...

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 higher-order model generator KIMBA.

This paper presents intial work on a system that bridges from robust, broad-coverage 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.

Godot is a mobile robot platform that serves as a testbed for the interface between a sophisticated lowlevel robot navigation and a symbolic high-level 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.

Contents 1 Introduction 1 2 Model Building 3 2.1 First-Order 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

... 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 first-order theorem provers to carry out consistency checking of discourse representations is investigated.

The paper ivestigates nite model building for rst order logic. We consider two main categories of methods: Mace-type and Falcontype methods. The paper has two goals: rst, presenting several improvements and strategies for the basic Mace-type and Falcon-type algorithms, second, comparing the eciency of dierent methods. The improvements to the Mace-type algorithms are focused on decreasing the size of the propositional subtasks. A new cell selection heuristics is introduced for the Falcon-type 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.

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 higher-order 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 ...

We have used the first-order model-searching 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