Agent Development Project

1 2004, G.Tecuci, Learning Agents Center

CS 7850 Fall 2004

Learning Agents Center and Computer Science Department

George Mason University

Gheorghe Tecuci [email protected]

http://lac.gmu.edu/


Schedule for the rest of the courseSchedule for the rest of the course

• November 18th Principles for designing instructible agents. Course review through exercises (in preparation for the final exam).

• December 2nd Discussion of open research issues. Projects presentations.

• December 9th Project presentations.

• December 16th Final Exam


Individual assignmentIndividual assignment

• It is expected that each of you has used the modules of Disciple to learn the rules corresponding to John Doe. You will receive credit for having done this.

• For this assignment you may use the knowledge base “PhD-Adv-learn”.

• Introduce the folder “PhD-Adv-learn” (received by email from the instructor) in the folder “\Disciple-RKF\Repository”

• Interact with Disciple to refine the rules corresponding to the other potential advisors from the knowledge base, as indicated in the following viewgraphs.

Due date: November 18th, 2004 (to do part of the assignment) and December 2nd (to finish it).


Review agent’s reasoning for the other potential advisorsReview agent’s reasoning for the other potential advisors

1. Start Disciple2. Use KB Manager (under the Domain menu) to open PhD-Adv-04 (under PhD-Adv-refine)3. Select Modules/Teaching4. Select the top level task and click-on the “Expand All” button from the bottom of the screen.5. Follow the agents reasoning for the other potential advisors. The agent performed this reasoning by using the rules learned from analyzing John Doe.











Critically examine the reasoning of the agentCritically examine the reasoning of the agent

1. Many of the task reduction steps of the agent are correct, but some may be incorrect.2. Use Ontology/Association Browser to review the description of Dan Smith (Use the Find button to find his description)3. Based on this description the reasoning of the agent is correct.4. Let us now assume, however, that we learn that Dan Smith is going to retire soon. 5. We would like to teach the agent that this disqualifies Dan Smith.6. We will switch to the refining mode by clicking the “Refining” button, at the bottom of the screen.




Incorrect ExampleIncorrect Example

Select the question/answer paper

Click on “Incorrect Example”


Use “Advanced” explanation, specifying a new feature:“is likely to obtain position”Type “ret”, then press “Ctrl” and keep it pressed and press “.”Disciple will show you the instances from KB that contain “ret” Select “retired_position”Press Create


Click on this task


You may provide here other values for the feature “is likely to obtain position”

For instance, you may indicate that Jill Knox is likely to get a tenured position.

At the end click “Apply” and then “Close” to close this tool.


Notice the “Except When” explanation added.Then click on “End Refining” and notice that the tasks

corresponding to Dan Smith are no longer reduced.


Use the Association Browser (or the Feature Browser) to view the learned feature:


Select the corresponding step for John Doe.Click on “View Rule” and notice how the rule was

refined by the addition of an Except-When condition.

Documents

Agent Development Project