Reduxexp: An Open-source Justiﬁcation-based Explanation Support Server

transcript

Reduxexp: An Open-source Justification-based Explanation Support Server

Thomas Roth-Berghofer & Florian MittagSenior researcher, trb@dfki.de German Research Centre for Artificial Intelligence DFKI GmbH

CAMBRIDGE, UK, 11 DEC 2008

Samstag, 18. Juli 2009

What are explanations?

What are explanations?Explanations are answers to questions.

Explanations are a kind of information.

Concepts connected with the notion of information

THE COACH TO STANSTED AIRPORT LEAVES

CAMBRIDGE AT 17:30 H.

• Truth

• Understanding

• Truth

• Understanding

• Utility

• Truth

• Understanding

• Utility

• Storage and retrieval

• Truth

• Understanding

• Utility

• Information generation

• Truth

• Understanding

• Utility

• Information generation

Basic explanation scenario

Knowledge sources

Problem solving

knowledge

Knowledge sources

Problem solving

knowledge

Explanation

knowledge

Knowledge sources

Problem solving

knowledge

Explanation

knowledge

Knowledge sources

Example: course assignment

• Professors Descartes and Kant

• Descartes more senior than Kant

• Heuristics:• Try to assign a course to the professor who wants

to teach that course.

• Assign courses to senior professors first.

• Preferences:• Descartes wants to teach course PHL305.

• Kant also wants to teach course PHL305.

• Kant would also teach course PHL380.Immanuel Kant

1724–1804

René Descartes1596–1650

Example: course assignment

• Decisions:• Descartes will teach PHL305.

• Kant will teach PHL380.

• What happens if Descartes could not teach PHL305?

Immanuel Kant 1724–1804

René Descartes1596–1650

Justification-based Truth Maintenance Systems

• Network of nodes and justifications, which are labelled IN or OUT:• Node is labelled IN <=> at least one of its supporting

justifications is labelled IN

• Justification is labelled IN <=> each element in its IN-list is labelled IN and each element in its OUT-list i labelled OUT

G1Conflict

Decision

G1Conflict

Decision

Reduction

G1Conflict

Decision

Reduction

A1, A2, …

G1Conflict

Decision

Reduction

A1, A2, …

: Goal reduction

Reduxexp Architecture

• Provenance• who decided

• and when

• Persistence• serialisation of network

into RDF/XML

Example:course assignment

• Kant enquires about his assignment:

FOR EACH assignment IN redux.getAllAssignments() { IF assignment.getName() == "Kant teaches PHL305" RETURN assignment; } IF assignment != null PRINT assignment.isValid();

• Kant: “Why didn’t I get to teach PHL305?”decisions[] = redux.getDecisionsForAssignment(assignment);

rejections[] = decisions[0].getRejectionReasons();

ReduxReason rejection = rejections[0]; PRINT "Assignments: "; FOR EACH a IN rejection.getConditionAssignments { PRINT a.getName() + " by " + a.getCreator(); } PRINT "Facts: "; FOR EACH f IN rejection.getConditionFacts { PRINT f.getName() + " by " + f.getCreator(); } PRINT "Rejected decisions: "; FOR EACH d IN rejection.getConditionDecisions { PRINT d.getName() + " by " + d.getCreator(); }

• Output:Assignments: "Descartes teaches PHL305" by ’Administrator’ Facts: "At most one teacher per course" by ’Administrator’ Rejected decisions: none

• Reduxexp does not generate explanations, it supports the process by providing the necessary information

• Client application supplies semantics.

Take home messages

• Explanations are important for increasing the trustworthiness of decision support systems.

Take home messages

• Explanations are part of communication scenario.

Take home messages

Explainer

Originator

• Explanation provision is only possible if the respective information is available.

Take home messages

Explainer

Originator

• Explanation provision is only possible if the respective information is available.

• Reduxexp is a server for logging / recording decisions.

Take home messages

Explainer

Originator

MORE INFORMATION AND DOWNLOAD: HTTP://REDUXEXP.OPENDFKI.DE

Thomas Roth-Berghofer & Florian MittagSenior researcher, trb@dfki.de German Research Centre for Artificial Intelligence DFKI GmbH

Thank you!

Reduxexp: An Open-source Justification-based Explanation Support Server

CAMBRIDGE, UK, 11 DEC 2008

Invitation to participate

• ExaCt mailing list:http://groups.yahoo.com/group/explanation-research/

• ExaCt 2009 @ IJCAI 2009 http://exact2009.workshop.hm

Publications of ExaCt research group

[Bahls, 2008] Bahls, D. (2008). Explanation support for the case-based reasoning tool myCBR. Project thesis, University of Kaiserslautern.

[Forcher et al., 2008] Forcher, B., Adrian, B., and Roth-Berghofer, T. (2008). Explanations in the information extraction system iDocument. Künstliche Intelligenz, 22(2).

[Mittag, 2008] Mittag, F. (2008). ReduxExp: A justification-based explanation-support server. Project thesis, University of Kaiserslautern.

[Roth-Berghofer and Bahls, 2008] Roth-Berghofer, T. R. and Bahls, D. (2008). Code tagging and retrieval with myCBR. In Petridis, M., Coenen, F., and Bramer, M., editors, Research and Development in Intelligent Systems XXV, London, UK. Springer Verlag.

[Roth-Berghofer and Mittag, 2008] Roth-Berghofer, T. R. and Mittag, F. (2008). ReduxExp: A justification-based explanation-support server. Proceedings of AI-2008. the twenty-eighth SGAI international conference on artificial intelligence. In Petridis, M., Coenen, F., and Bramer, M., editors, Research and Development in Intelligent Systems XXV, London, UK. Springer Verlag.

[Roth-Berghofer and Richter, 2008a] Roth-Berghofer, T. R. and Richter, M. M., editors (2008a). Künstliche Intelligenz—Topic: Explanation, volume 22, Bremen. BöttcherIT Verlag.

[Roth-Berghofer and Richter, 2008b] Roth-Berghofer, T. R. and Richter, M. M. (2008b). On explanation. Künstliche Intelligenz, 22(2):5–7.

[Bahls and Roth-Berghofer, 2007] Bahls, D. and Roth-Berghofer, T. (2007). Explanation support for the case-based reasoning tool myCBR. In Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence. July 22–26, 2007, Vancouver, British Columbia, Canada., pages 1844–1845. The AAAI Press, Menlo Park, California.

[Eppert, 2007] Eppert, M. (2007). Generating provenance explanations for the gnowsis rebirth machine - a first pass. Pro ject thesis, University of Kaiserslautern.

2007 (contd.)

[Roth-Berghofer et al., 2007] Roth-Berghofer, T. R., Schulz, S., and Leake, D. B., editors (2007). Proceedings of the AAAI-07 workshop on Explanation-aware Computing ExaCt2007. AAAI Press. Technical Report WS-07-06.

[Richter et al., 2006] Richter, M. M., Roth-Berghofer, T., and Schulz, S., editors (2006). Explanation-aware Computing, volume 25. SAP - Slovak Academic Press Ltd., Bratislava.

[Roth-Berghofer et al., 2005a] Roth-Berghofer, T., Cassens, J., and Sørmo, F. (2005a). Goals and kinds of explanations in case-based reasoning. In Althoff, K.-D., Dengel, A., Bergmann, R., Nick, M., and Roth-Berghofer, T., editors, WM 2005: Professional Knowledge Management, pages 264–268, Kaiserslautern, Germany. DFKI GmbH.

[Roth-Berghofer and Cassens, 2005] Roth-Berghofer, T. R. and Cassens, J. (2005). Mapping goals and kinds of explanations to the knowledge containers of case-based reasoning systems. In Muñoz-Avila, H. and Ricci, F., editors, Case-Based Reasoning Research and Developmen, pages 451–464, Heidelberg. Springer Verlag.

[Roth-Berghofer et al., 2005b] Roth-Berghofer, T. R., Schulz, S., and Woody, A., editors (2005b). Proceedings of the AAAI Fal l Symposium on Explanation-aware Computing ExaCt2005. AAAI Press. Technical Report FS-05-04.

[Roth-Berghofer, 2004] Roth-Berghofer, T. R. (2004). Explanations and Case-Based Reasoning: Foundational issues. In Funk, P. and González-Calero, P. A., editors, Advances in Case-Based Reasoning, pages 389–403. Springer-Verlag.

Reduxexp: An Open-source Justiﬁcation-based Explanation Support Server

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