Open AccessBook
User Interface
Eero Eloranta
- 01 Jan 1988
pp 181-199
68
TL;DR: Extensions to the user interface are described to support planning by analogical reasoning and probabilistic planning with PRODIGY to build a domain and animating the planning process.
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Abstract: The PRODIGY user interface supports the process of both building and running a planning domain in PRODIGY. It was designed to be highly modular, requiring no changes to the code of the PRODIGY planner to run, and extensible, so that interfaces to other modules built on PRODIGY could easily be integrated into the interface. In this paper we describe how these goals were achieved. We demonstrate building a domain and animating the planning process. We describe extensions to the user interface to support planning by analogical reasoning and probabilistic planning with PRODIGY. 1On leave from Escola Federal de Engenharia de Itajubá, MG, Brazil. Visiting researcher at CMUwith financial support provided byCNPq -ConselhoNacional deDesenvolvimentoCientı́fico e Tecnológico, Brası́lia, DF.
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Stephan Steglich
- 27 Nov 2003
TL;DR: The SMIL switch statement, GUIML supports the specification of a set of alternative media elements from which only the most suitable element is chosen, such as the user’s preferences.
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Handheld haptics: a USB media controller with force sensing
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An intelligent tutoring system architecture based on fuzzy neural network (FNN) for special education of learning disabled learners
TL;DR: The results indicate that the integration of fuzzy with the neural network has significantly increased the ITS accuracy.
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References
•Book
Derivational analogy: a theory of reconstructive problem solving and expertise acquisition
Jaime G. Carbonell
- 02 Jan 1993
TL;DR: Derivational analogy, a method of solving problems based on the transfer of past experience to new problem situations, is discussed in the context of other general approaches to problem solving.
•Proceedings Article
Non-Intrusive Gaze Tracking Using Artificial Neural Networks
Shumeet Baluja,Dean A. Pomerleau +1 more
- 29 Nov 1993
TL;DR: An empirical analysis of the performance of a large number of artificial neural network architectures for gaze tracking, and Suggestions for further explorations for neurally based gaze trackers are presented, and are related to other similar artificial Neural network applications such as autonomous road following.
Integrating planning and learning: the PRODIGY architecture
TL;DR: This article describes the PRODIGY planner, briefly reports on several learning modules developed earlier along the project, and presents in more detail two recently explored methods to learn to generate plans of better quality.
Planning for Machining Workpieces with a Partial-Order, Nonlinear Planner
Juergen Paulokat,Stefan Wess +1 more
- 01 Jan 1999
TL;DR: A case-based control component has been realized that allows incremental acquisition of control knowledge by storing solved problems and reusing them in similar situations to make planning more efficient.
19
Planning and reacting in uncertain and dynamic environments
TL;DR: The Cypress system is a domain-independent framework for defining persistent agents with this full range of behaviour, used for several demanding applications, including military operations, real-time tracking, and fault diagnosis.
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