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.

1. CAMBRIDGE, UK, 11 DEC 2008
Redux exp: An
Open-source Justification-
based Explanation Support Server
Thomas Roth-Berghofer & Florian Mittag
Senior researcher, trb@dfki.de
German Research Centre for Artificial Intelligence DFKI GmbH
Samstag, 18. Juli 2009

2. What are
explanations?
Samstag, 18. Juli 2009

3. What are
explanations?
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4. What are
explanations?
Explanations
are answers to
questions.
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5. Explanations are a kind
of information.
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6. Concepts connected with the
notion of information
THE COACH TO STANSTED
AIRPORT LEAVES
CAMBRIDGE AT 17:30 H.
Samstag, 18. Juli 2009

7. Concepts connected with the
notion of information
• Truth
THE COACH TO STANSTED
AIRPORT LEAVES
CAMBRIDGE AT 17:30 H.
Samstag, 18. Juli 2009

8. Concepts connected with the
notion of information
• Truth
• Understanding
THE COACH TO STANSTED
AIRPORT LEAVES
CAMBRIDGE AT 17:30 H.
Samstag, 18. Juli 2009

9. Concepts connected with the
notion of information
• Truth
• Understanding
THE COACH TO STANSTED
AIRPORT LEAVES • Utility
CAMBRIDGE AT 17:30 H.
Samstag, 18. Juli 2009

10. Concepts connected with the
notion of information
• Truth
• Understanding
THE COACH TO STANSTED
AIRPORT LEAVES • Utility
CAMBRIDGE AT 17:30 H. • Storage and
retrieval
Samstag, 18. Juli 2009

11. Concepts connected with the
notion of information
• Truth
• Understanding
THE COACH TO STANSTED
AIRPORT LEAVES • Utility
CAMBRIDGE AT 17:30 H. • Storage and
retrieval
• Information
generation
Samstag, 18. Juli 2009

12. Concepts connected with the
notion of information
• Truth
• Understanding
THE COACH TO STANSTED
AIRPORT LEAVES • Utility
CAMBRIDGE AT 17:30 H. • Storage and
retrieval
• Information
generation
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13. Basic explanation scenario
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14. Knowledge sources
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15. Problem solving
knowledge
Knowledge sources
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16. Explanation
knowledge
Problem solving
knowledge
Knowledge sources
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17. Explanation
knowledge
Problem solving
knowledge
Knowledge sources
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18. Example:
course assignment
• Professors Descartes and Kant
• Descartes more senior than Kant
René Descartes
• Heuristics: 1596–1650
• 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.
Immanuel Kant
• Kant would also teach course PHL380. 1724–1804
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19. Example:
course assignment
• Decisions: René Descartes
1596–1650
• Descartes will teach PHL305.
• Kant will teach PHL380.
• What happens if Descartes could
not teach PHL305?
Immanuel Kant
1724–1804
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20. 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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21. REDUX
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22. REDUX
G1
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23. REDUX
G1
O1
O2
…
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24. REDUX
G1
Conflict
set
O1
O2
…
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25. REDUX
G1
Conflict
set
O1
Decision
O2
…
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26. REDUX
G1
Conflict
set
O1
Decision
O2
…
Reduction
…
G2 Gn
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27. REDUX
G1
Conflict
set
O1
Decision
O2
…
Reduction
…
G2 Gn A1, A2, …
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28. REDUX : Goal reduction
G1
Conflict
set
O1
Decision
O2
…
Reduction
…
G2 Gn A1, A2, …
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29. Redux exp Architecture
• Provenance
• who decided
• and when
• Persistence
• serialisation of network
into RDF/XML
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30. Example:
course assignment
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31. Example:
course assignment
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32. Example:
course assignment
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33. Example:
course assignment
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34. Example:
course assignment
• Kant enquires about his assignment:
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35. 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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36. Example:
course assignment
• Kant: “Why didn’t I get to teach PHL305?”
decisions[] = redux.getDecisionsForAssignment(assignment);
Samstag, 18. Juli 2009

37. Example:
course assignment
• Kant: “Why didn’t I get to teach PHL305?”
decisions[] = redux.getDecisionsForAssignment(assignment);
rejections[] = decisions[0].getRejectionReasons();
Samstag, 18. Juli 2009

38. 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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39. 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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40. 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
Samstag, 18. Juli 2009

41. 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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42. Take home messages
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43. Take home messages
• Explanations are important for
increasing the trustworthiness of
decision support systems.
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44. Take home messages
• Explanations are important for Explainer
increasing the trustworthiness of
User
decision support systems.
Originator
• Explanations are part of
communication scenario.
Samstag, 18. Juli 2009

45. Take home messages
• Explanations are important for Explainer
increasing the trustworthiness of
User
decision support systems.
Originator
• Explanations are part of
communication scenario.
• Explanation provision is only possible
if the respective information is
available.
Samstag, 18. Juli 2009

46. Take home messages
• Explanations are important for Explainer
increasing the trustworthiness of
User
decision support systems.
Originator
• 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.
MORE INFORMATION AND DOWNLOAD:
HTTP://REDUXEXP.OPENDFKI.DE
Samstag, 18. Juli 2009

47. Thank you!
CAMBRIDGE, UK, 11 DEC 2008
Redux exp: An
Open-source Justification-
based Explanation Support Server
Thomas Roth-Berghofer & Florian Mittag
Senior researcher, trb@dfki.de
German Research Centre for Artificial Intelligence DFKI GmbH
Samstag, 18. Juli 2009

48. Invitation to participate
• ExaCt mailing list:
http://groups.yahoo.com/group/explanation-research/
• ExaCt 2009 @ IJCAI 2009
http://exact2009.workshop.hm
Samstag, 18. Juli 2009

49. Publications of ExaCt
research group
2008 2007 (contd.)
[Bahls, 2008] Bahls, D. (2008). Explanation support for the case-based [Roth-Berghofer et al., 2007] Roth-Berghofer, T. R., Schulz, S., and Leake,
reasoning tool myCBR. Project thesis, University of Kaiserslautern. D. B., editors (2007). Proceedings of the AAAI-07 workshop on
[Forcher et al., 2008] Forcher, B., Adrian, B., and Roth-Berghofer, T. (2008). Explanation-aware Computing ExaCt2007. AAAI Press. Technical Report
Explanations in the information extraction system iDocument. Künstliche WS-07-06.
Intelligenz, 22(2). 2006
[Mittag, 2008] Mittag, F. (2008). ReduxExp: A justification-based [Richter et al., 2006] Richter, M. M., Roth-Berghofer, T., and Schulz, S.,
explanation-support server. Project thesis, University of Kaiserslautern. editors (2006). Explanation-aware Computing, volume 25. SAP - Slovak
[Roth-Berghofer and Bahls, 2008] Roth-Berghofer, T. R. and Bahls, D. Academic Press Ltd., Bratislava.
(2008). Code tagging and retrieval with myCBR. In Petridis, M., Coenen, F., 2005
and Bramer, M., editors, Research and Development in Intelligent Systems [Roth-Berghofer et al., 2005a] Roth-Berghofer, T., Cassens, J., and Sørmo,
XXV, London, UK. Springer Verlag. F. (2005a). Goals and kinds of explanations in case-based reasoning. In
[Roth-Berghofer and Mittag, 2008] Roth-Berghofer, T. R. and Mittag, F. Althoff, K.-D., Dengel, A., Bergmann, R., Nick, M., and Roth-Berghofer, T.,
(2008). ReduxExp: A justification-based explanation-support server. editors, WM 2005: Professional Knowledge Management, pages 264–268,
Proceedings of AI-2008. the twenty-eighth SGAI international conference Kaiserslautern, Germany. DFKI GmbH.
on artificial intelligence. In Petridis, M., Coenen, F., and Bramer, M., editors,
[Roth-Berghofer and Cassens, 2005] Roth-Berghofer, T. R. and Cassens, J.
Research and Development in Intelligent Systems XXV, London, UK.
(2005). Mapping goals and kinds of explanations to the knowledge
Springer Verlag.
containers of case-based reasoning systems. In Muñoz-Avila, H. and Ricci,
[Roth-Berghofer and Richter, 2008a] Roth-Berghofer, T. R. and Richter, M. F., editors, Case-Based Reasoning Research and Developmen, pages 451–
M., editors (2008a). Künstliche Intelligenz—Topic: Explanation, volume 22, 464, Heidelberg. Springer Verlag.
Bremen. BöttcherIT Verlag.
[Roth-Berghofer et al., 2005b] Roth-Berghofer, T. R., Schulz, S., and
[Roth-Berghofer and Richter, 2008b] Roth-Berghofer, T. R. and Richter, M. Woody, A., editors (2005b). Proceedings of the AAAI Fal l Symposium on
M. (2008b). On explanation. Künstliche Intelligenz, 22(2):5–7. Explanation-aware Computing ExaCt2005. AAAI Press. Technical Report
2007 FS-05-04.
[Bahls and Roth-Berghofer, 2007] Bahls, D. and Roth-Berghofer, T. (2007). 2004
Explanation support for the case-based reasoning tool myCBR. In [Roth-Berghofer, 2004] Roth-Berghofer, T. R. (2004). Explanations and
Proceedings of the Twenty-Second AAAI Conference on Artificial Case-Based Reasoning: Foundational issues. In Funk, P. and González-
Intelligence. July 22–26, 2007, Vancouver, British Columbia, Canada., Calero, P. A., editors, Advances in Case-Based Reasoning, pages 389–403.
pages 1844–1845. The AAAI Press, Menlo Park, California. Springer-Verlag.
[Eppert, 2007] Eppert, M. (2007). Generating provenance explanations for
the gnowsis rebirth machine - a first pass. Pro ject thesis, University of
Kaiserslautern.
Samstag, 18. Juli 2009