reduxexp: an open-source justification-based explanation support server
DESCRIPTION
Trust in any decision depends on many factors. One way of improving trust is by explaining why a certain decision has been made and how certain actions in the context of a decision have been performed. In order to provide such explanations information systems need a mechanism for recording decisions and actions. The open-source server Reduxexp is such a system. This paper describes the architecture of Reduxexp and first experiences with the system.TRANSCRIPT
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Reduxexp: An Open-source Justification-based Explanation Support Server
Thomas Roth-Berghofer & Florian MittagSenior researcher, [email protected] German Research Centre for Artificial Intelligence DFKI GmbH
CAMBRIDGE, UK, 11 DEC 2008
Samstag, 18. Juli 2009
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What are explanations?
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What are explanations?
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What are explanations?Explanations are answers to questions.
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Explanations are a kind of information.
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Concepts connected with the notion of information
THE COACH TO STANSTED AIRPORT LEAVES
CAMBRIDGE AT 17:30 H.
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• Truth
Concepts connected with the notion of information
THE COACH TO STANSTED AIRPORT LEAVES
CAMBRIDGE AT 17:30 H.
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• Truth
• Understanding
Concepts connected with the notion of information
THE COACH TO STANSTED AIRPORT LEAVES
CAMBRIDGE AT 17:30 H.
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• Truth
• Understanding
• Utility
Concepts connected with the notion of information
THE COACH TO STANSTED AIRPORT LEAVES
CAMBRIDGE AT 17:30 H.
Samstag, 18. Juli 2009
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• Truth
• Understanding
• Utility
• Storage and retrieval
Concepts connected with the notion of information
THE COACH TO STANSTED AIRPORT LEAVES
CAMBRIDGE AT 17:30 H.
Samstag, 18. Juli 2009
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• Truth
• Understanding
• Utility
• Storage and retrieval
• Information generation
Concepts connected with the notion of information
THE COACH TO STANSTED AIRPORT LEAVES
CAMBRIDGE AT 17:30 H.
Samstag, 18. Juli 2009
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• Truth
• Understanding
• Utility
• Storage and retrieval
• Information generation
Concepts connected with the notion of information
THE COACH TO STANSTED AIRPORT LEAVES
CAMBRIDGE AT 17:30 H.
Samstag, 18. Juli 2009
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Basic explanation scenario
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Knowledge sources
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Problem solving
knowledge
Knowledge sources
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Problem solving
knowledge
Explanation
knowledge
Knowledge sources
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Problem solving
knowledge
Explanation
knowledge
Knowledge sources
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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
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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
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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
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REDUX
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REDUX
G1
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REDUX
G1
O1
O2
…
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REDUX
G1Conflict
set
O1
O2
…
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REDUX
G1Conflict
set
Decision
O1
O2
…
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REDUX
G1Conflict
set
Decision
Reduction
O1
O2
…
GnG2
…
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REDUX
G1Conflict
set
Decision
Reduction
A1, A2, …
O1
O2
…
GnG2
…
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REDUX
G1Conflict
set
Decision
Reduction
A1, A2, …
O1
O2
…
GnG2
…
: Goal reduction
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Reduxexp Architecture
• Provenance• who decided
• and when
• Persistence• serialisation of network
into RDF/XML
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Example:course assignment
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Example:course assignment
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Example:course assignment
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Example:course assignment
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Example:course assignment
• Kant enquires about his assignment:
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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();
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Example:course assignment
• Kant: “Why didn’t I get to teach PHL305?”decisions[] = redux.getDecisionsForAssignment(assignment);
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Example:course assignment
• Kant: “Why didn’t I get to teach PHL305?”decisions[] = redux.getDecisionsForAssignment(assignment);
rejections[] = decisions[0].getRejectionReasons();
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Example:course assignment
• 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(); }
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Example:course assignment
• Output:Assignments: "Descartes teaches PHL305" by ’Administrator’ Facts: "At most one teacher per course" by ’Administrator’ Rejected decisions: none
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Example:course assignment
• Output:Assignments: "Descartes teaches PHL305" by ’Administrator’ Facts: "At most one teacher per course" by ’Administrator’ Rejected decisions: none
Note:
• Reduxexp does not generate explanations, it supports the process by providing the necessary information
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Example:course assignment
• Output:Assignments: "Descartes teaches PHL305" by ’Administrator’ Facts: "At most one teacher per course" by ’Administrator’ Rejected decisions: none
Note:
• Reduxexp does not generate explanations, it supports the process by providing the necessary information
• Client application supplies semantics.
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Take home messages
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• Explanations are important for increasing the trustworthiness of decision support systems.
Take home messages
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• Explanations are important for increasing the trustworthiness of decision support systems.
• Explanations are part of communication scenario.
Take home messages
Explainer
Originator
User
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• Explanations are important for increasing the trustworthiness of decision support systems.
• Explanations are part of communication scenario.
• Explanation provision is only possible if the respective information is available.
Take home messages
Explainer
Originator
User
Samstag, 18. Juli 2009
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• Explanations are important for increasing the trustworthiness of decision support systems.
• Explanations are part of communication scenario.
• Explanation provision is only possible if the respective information is available.
• Reduxexp is a server for logging / recording decisions.
Take home messages
Explainer
Originator
User
MORE INFORMATION AND DOWNLOAD: HTTP://REDUXEXP.OPENDFKI.DE
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Thomas Roth-Berghofer & Florian MittagSenior researcher, [email protected] German Research Centre for Artificial Intelligence DFKI GmbH
Thank you!
Reduxexp: An Open-source Justification-based Explanation Support Server
CAMBRIDGE, UK, 11 DEC 2008
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Invitation to participate
• ExaCt mailing list:http://groups.yahoo.com/group/explanation-research/
• ExaCt 2009 @ IJCAI 2009 http://exact2009.workshop.hm
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Publications of ExaCt research group
2008
[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.
2007
[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.
2006
[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.
2005
[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.
2004
[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.
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