Modeling Confidence for Assistant Systems

Modeling Confidence for Assistant Systems

Roland Kaschek (Massey University, New Zealand)
DOI: 10.4018/978-1-59140-878-9.ch004
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An intelligent assistant system is supposed to relatively autonomously aid a master in problem solving. The way of doing so that is favored in this chapter involves master-assistant communication that leads to the assistant being exposed to a goal the master wants to achieve. The assistant—if that is possible—then creates problem solution procedures, the implementation of which is supposed to result in the goal being achieved. The assistant then chooses an implementation that can be expected to fit well its master dispositions. An assistant thus needs to know parts of its master’s cognitive structure and to be capable of reasoning about it. The chapter proposes to use models as composite verdictive entities by means of which a master may refer to a domain of individuals. The concept of judgment is assumed to be the simple verdictive entity out of which models are composed. Models are used for representing cognitive states of masters. In particular, model extensions are considered, that is, models that are closed with respect to predicate negation of judgments, conjunction of judgments, and conditional judgments. The concept of confidence is formalized and applied to model extensions for deriving quantitative assertions about judgments. It is briefly discussed how the proposed theory of confidence in judgments can be used in intelligent assistant systems.

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Table of Contents
Roland Kaschek
Chapter 1
Gunter Grieser, Steffen Lange
This chapter deals with the question of how the interaction between humans and computers may be designed to enable both partners to bring in their... Sample PDF
Interaction Scenarios for Information Extraction
Chapter 2
Klaus Jantke, Nataliya Lamonova
Software systems on their way from tools to assistants have to be equipped with learnability. This does apply in complex problem solving... Sample PDF
Assistance and Induction: The Therapy Planning Case
Chapter 3
Klaus Jantke, Carsten Müller
These days, search engines are useful tools relying on quite elaborated technologies which, albeit their enormous frequency of usage and the... Sample PDF
Wrapper Induction Programs as Information Extraction Assistants
Chapter 4
Roland Kaschek
An intelligent assistant system is supposed to relatively autonomously aid a master in problem solving. The way of doing so that is favored in this... Sample PDF
Modeling Confidence for Assistant Systems
Chapter 5
Son B. Pham, Achim Hoffmann
In this chapter we discuss ways of assisting experts to develop complex knowledge bases for a variety of natural language processing tasks. The... Sample PDF
Intelligent Support for Building Knowledge Bases for Natural Language Processing
Chapter 6
Klaus-Dieter Schewe, Bernhard Thalheim, Alexei Tretiakov
The aim of this chapter is to formalize user preferences, obligations, and rights in the context of Web information systems (WISs), and to indicate... Sample PDF
Formalization of User Preferences, Obligations and Rights
Chapter 7
Kimihito Ito
This chapter introduces a software architecture to build intelligent multimodal assistants. The architecture consists of three basic components: a... Sample PDF
Building Intelligent Multimodal Assistants Based on Logic Programming in the Meme Media Architecture
Chapter 8
Nataliya Lamonova, Kimihito Ito, Yuzura Tanaka
This chapter introduces an approach for creating Web application capable of operating in complex environments is introduced. The approach shows how... Sample PDF
From Planning Tools to Intelligent Assistants: Meme Media and Logic Programming Technologies
Chapter 9
Yuzura Tanaka
The current Web is a mine of tools and services and the gate to ubiquitous computing environments with a huge number of highly distributed mobile... Sample PDF
Memetic Approach to the Location-Based Ad Hoc Federation of Intelligent Resources
Chapter 10
Klaus Jantke, Christoph Igel, Roberta Sturm
Humans need assistance in learning. This is particularly true when learning is supported by modern information and communication technologies. Most... Sample PDF
From E-Learning Tools to Assistants by Learner Modelling and Adaptive Behavior
Chapter 11
Sabina Jeschke, Thomas Richter
The workplace of scientists and engineers is about to change: even though numerical software and computer algebra systems remove the burden of... Sample PDF
Mathematics in Virtual Knowledge Spaces: User Adaptation by Intelligent Assistants
Chapter 12
Alexander Krumpholz
This chapter describes the virtual trainer we developed for CSIRO’s temporal bone dissection simulator. This simulation software runs on an... Sample PDF
Building a Virtual Trainer for an Immersive Haptic Virtual Reality Environment
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