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Knowledge Acquisition and Problem Solving

This presentation by Gheorghe Tecuci showcases the advanced capabilities of the DISCIPLE-RKF system for modeling the reasoning processes of subject matter experts. The system allows users to interact with a reasoning tree, refine it with various tasks, and engage with the Modeling Advisor for enhanced learning experiences. Users can expand the reasoning tree, model new solutions, and receive suggestions for questions and tasks, facilitating a better understanding of knowledge acquisition and problem-solving methodologies. Explore the innovative approaches in learning agents at George Mason University.

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Knowledge Acquisition and Problem Solving

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  1. CS 785 Fall 2004 Knowledge Acquisition and Problem Solving Demo: Modeling the Reasoning of a Subject Matter Expert Gheorghe Tecuci tecuci@gmu.eduhttp://lac.gmu.edu/ Learning Agents Center and Computer Science Department George Mason University

  2. DISCIPLE-RKF Disciple-RKF/COG: Agent Teaching and Rule Learning

  3. To view the reasoning tree You may click on the arrows to minimize/maximize the reasoning tree view

  4. To refine the reasoning tree Click on the task solve Click on “Expand All”

  5. To start modeling a new solution Select the task that needs to be reduced to simpler tasks Click on “Modeling” to go to the Modeling Advisor

  6. Modeling a reasoning step Read and follow the suggestions from this panel You may select other options from this panel Type your modeling here

  7. Recognizing and completing elements You should attempt to use these names whenever possible When you are starting a new name The system attempts to guess it

  8. Finishing the question When finished typing,press ENTER

  9. Suggesting answers Sometimes the system suggests answers, questions, or tasks. You may select one of them and may modify it. To return to the reasoning tree, click on “Close”

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