Configuration Knowledge Representation and Reasoning

Knowledge-Based Configuration: From Research to Business Cases

Volumn , Issue , 2014, Pages 41-72

  Hotz, Lothar ^a   Felfernig, Alexander ^b   Stumptner, Markus ^c   Ryabokon, Anna ^d   Bagley, Claire ^e   Wolter, Katharina ^a  

^a UNIVERSITY OF HAMBURG   (Germany)

^b GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

^c UNIVERSITY OF SOUTH AUSTRALIA   (Australia)

^d UNIVERSITY OF KLAGENFURT   (Austria)

^e ORACLE CORPORATION   (United States)

Author keywords

Answer Set Programming; Constraints; Description Logics; Feature Models; Knowledge Representation; Knowledge based Configuration; Unified Modelling Language

Indexed keywords

COMPUTER PROGRAMMING; DATA DESCRIPTION; KNOWLEDGE BASED SYSTEMS; LOGIC PROGRAMMING; MODELING LANGUAGES; PERSONAL COMPUTERS; PRODUCT DESIGN; UNIFIED MODELING LANGUAGE;

ANSWER SET PROGRAMMING; CONSTRAINTS; DESCRIPTION LOGIC; FEATURE MODELS; KNOWLEDGE BASED;

KNOWLEDGE REPRESENTATION;

EID: 84902216801     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1016/B978-0-12-415817-7.00006-2     Document Type: Chapter

References (77)

1. Amilhastre J., Fargier H., Marquis P. Consistency restoration and explanations in dynamic CSPs - application to configuration. Artificial Intelligence 2002, 135(1-2):199-234.
2. Andersen H., Hadzic T., Pisinger D. Interactive cost configuration over decision diagrams. Journal of Artificial Intelligence Research 2010, 37:99-139.
3. The Description Logic Handbook: Theory, Implementation, and Applications 2003, Cambridge University Press, New York, NY. F. Baader, D. Calvanese, D.L. McGuinness, D. Nardi, P.F. Patel-Schneider (Eds.).
4. Bacchus F., vanBeek P. On the conversion between non-binary and binary constraint satisfaction problems. 15th National Conference on Artificial Intelligence (AAAI'98). Madison, Wisconsin 1998, 311-318.
5. Batory D. Feature models, grammars, and propositional formulas. Lecture Notes in Computer Science 2005, vol. 3714:7-20. Springer, Rennes, France. H. Obbink, K. Pohl (Eds.).
6. Benavides D., Segura S., Ruiz-Cortés A. Automated analysis of feature models 20 years later: a literature review. Information Systems 2010, 35(6):615-636.
7. Booch G., Rumbaugh J., Jacobson I. Unified Modeling Language User Guide 2005, Addison-Wesley, Reading, MA. second ed.
8. Bowen J., Bahler D. Conditional existence of variables in generalized constraint networks. 9th National Conference on Artificial Intelligence (AAAI-91). Anaheim, California 1991, 215-220.
9. Brailsford S., Potts C., Smith B. Constraint satisfaction problems: algorithms and applications. European Journal of Operational Research 1999, 199(3):557-581.
10. Brewka G., Eiter T., Truszczyński M. Answer set programming at a glance. Communications of the ACM 2011, 54(12):92-103.
11. Buchheit, M., Klein, R., Nutt, W., 1995. Constructive Problem Solving: A Model Construction Approach Towards Configuration, Deutsches Forschungszentrum für Künstliche Intelligenz, Saarbrücken (TM-95-01).
12. Claessen K., Een N., Sheeran M., Sörensson N. SAT-solving in practice. 9th International Workshop on Discrete Event Systems. Göteborg, Sweden 2008, 61-67.
13. Czarnecki K., Helsen S., Eisenecker U. Formalizing cardinality-based feature models and their specialization. SoftwareProcess: Improvement and Practice 2005, 10(1):7-29.
14. Falkner A., Haselböck A. Challenges of knowledge evolution in practice. AI Communications 2013, 26(1):3-14.
15. Falkner A., Schreiner H. SIEMENS: configuration and reconfiguration in industry. Knowledge-based Configuration - From Research to Business Cases 2014, 199-210. Morgan Kaufmann Publishers, Waltham, MA, (Chapter 16). A. Felfernig, L. Hotz, C. Bagley, J. Tiihonen (Eds.).
16. Falkner A., Felfernig A., Haag A. Recommendation technologies for configurable products. AI Magazine 2011, 32(3):99-108.
17. Faltings, B., Weigel, R., 1994. Constraint-based knowledge representation for configuration systems. Tech. Rep. TR-94/59, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
18. Felfernig A. Standardized configuration knowledge representations as technological foundation for mass customization. IEEE Transactions on Engineering Management 2007, 54(1):41-56.
19. Felfernig A., Burke R. Constraint-based recommender systems: technologies and research issues. ACM International Conference on Electronic Commerce (ICEC08). Innsbruck, Austria 2008, 17-26.
20. Felfernig A., Zanker M. Diagrammatic acquisition of functional knowledge for product configuration systems with the unified modeling language. Lecture Notes in Computer Science 2000, vol. 1889:361-375. Springer-Verlag, London, UK.
21. Felfernig A., Friedrich G.E., Jannach D. UML as domain specific language for the construction of knowledge-based configuration systems. International Journal of Software Engineering and Knowledge Engineering 2000, 10(4):449-469.
22. Felfernig A., Jannach D., Zanker M. Contextual diagrams as structuring mechanisms for designing configuration knowledge bases in UML. Lecture Notes in Computer Science 2000, Vol. 1939:240-254. Springer, York, UK.
23. Felfernig A., Friedrich G., Jannach D. Conceptual modeling for configuration of mass-customizable products. Artificial Intelligence in Engineering 2001, 15(2):165-176.
24. Felfernig A., Friedrich G., Jannach D., Stumptner M., Zanker M. Configuration knowledge representations for semantic web applications. Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AI EDAM) 2003, 17(1):31-50.
25. Felfernig A., Friedrich G., Jannach D., Stumptner M. Consistency-based diagnosis of configuration knowledge bases. Artificial Intelligence 2004, 152(2):213-234.
26. Felfernig A., Schubert M., Zehentner C. An efficient diagnosis algorithm for inconsistent constraint sets. Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AI EDAM) 2012, 26(1):53-62.
27. Felfernig A., Benavides D., Galindo J., Reinfrank F. Towards anomaly explanation in feature models. Workshop on Configuration. Vienna, Austria 2013, 117-124.
28. Felfernig A., Reiterer S., Stettinger M., Reinfrank F., Jeran M., Ninaus G. Recommender systems for configuration knowledge engineering. Workshop on Configuration. Vienna, Austria 2013, 51-54.
29. Fleischanderl G., Friedrich G.E., Haselböck A., Schreiner H., Stumptner M. Configuring large systems using generative constraint satisfaction. IEEE Intelligent Systems 1998, 13(4):59-68.
30. Freuder E. In pursuit of the holy grail. Constraints 1997, 2(1):57-61.
31. Friedrich G., Jannach D., Stumptner M., Zanker M. Knowledge engineering for configuration systems. Knowledge-based Configuration - From Research to Business Cases 2014, 139-155. Morgan Kaufmann Publishers, Waltham, MA, (Chapter 11). A. Felfernig, L. Hotz, C. Bagley, J. Tiihonen (Eds.).
32. Gebser M., Kaminski R., Ostrowski M., Schaub T., Thiele S. On the input language of ASP grounder Gringo. Lecture Notes in Computer Science 2009, Vol. 5373:502-508. Springer, Potsdam, Germany. E. Erdem, F. Lin, T. Schaub (Eds.).
33. Gelfond M., Lifschitz V. The stable model semantics for logic programming. Logic Programming: Proceedings of the 5th International Conference and Symposium. Seattle, WA 1988, 1070-1080. R.A. Kowalkowski, K.A. Bowen (Eds.).
34. Giunchiglia E., Lierler Y., Maratea M. Answer set programming based on propositional satisfiability. Journal of Automated Reasoning 2006, 36(4):345-377.
35. Gomes C., Kautz H., Sabharwal A., Selman B. Satisfiability solvers. Foundations of Artificial Intelligence 2008, vol. 3:89-134. Elsevier, New York, NY, (Chapter 2).
36. Günter A., Kühn C. Knowledge-Based Configuration - Survey and Future Directions. Lecture Notes in Artificial Intelligence 1999, Vol. 1570. Springer, Würzburg. F. Puppe (Ed.).
37. Hotz L., Günter A. KONWERK. Knowledge-based Configuration - From Research to Business Cases 2014, 281-295. Morgan Kaufmann Publishers, Waltham, MA, (Chapter 24). A. Felfernig, L. Hotz, C. Bagley, J. Tiihonen (Eds.).
38. Hotz L., Neumann B. Scene Interpretation as a Configuration Task. Künstliche Intelligenz 2005, 3:59-65.
39. Hotz L., Wolter K. Smarthome Configuration Model. Knowledge-based Configuration - From Research to Business Cases 2014, 121-135. Morgan Kaufmann Publishers, Waltham, MA, (Chapter 10). A. Felfernig, L. Hotz, C. Bagley, J. Tiihonen (Eds.).
40. Hotz L., Wolter K., Krebs T., Deelstra S., Sinnema M., Nijhuis J., MacGregor J. Configuration in Industrial Product Families - The ConIPF Methodology 2006, IOS Press, Berlin.
41. Jannach D., Zanker M., Felfernig A., Friedrich G. Recommender Systems: An Introduction 2010, Cambridge University Press, MA.
42. Janota M. Do SAT solvers make good configurators?. First Workshop on Analyses of Software Product Lines (ASPL08) of 12th International Software Product Lines Conference (SPLC08). Limerick, Ireland 2008, 10-14.
43. Janota M., Botterweck G., Grigore R., Marques-Silva J. How to complete an interactive configuration process?. Lecture Notes in Computer Science 2010, vol. 5901:528-539. Springer, Špindlerův Mlýn, Czech Republic.
44. Jüngst W., Heinrich M. Using resource balancing to configure modular systems. IEEE Intelligent Systems 1998, 13(4):50-58.
45. Junker U. QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems. 19th Intl. Conference on Artifical Intelligence (AAAI'04) 2004, 167-172. AAAI Press. D.L. McGuinness, G. Ferguson (Eds.).
46. Junker U. Configuration. Foundations of Artificial Intelligence 2006, vol. 2:837-873. Elsevier, New York, NY. F. Rossi, P. vanBeek, T. Walsh (Eds.).
47. Junker U., Mailharro D. The logic of ILOG (J)Configurator: Combining constraint programming with a description logic. 18th International Joint Conference on Artificial Intelligence (IJCAI-03), Configuration Workshop. Acapulco, Mexico 2003, 13-20.
48. Kang, K., Cohen, S., Hess, J., Novak, W., Peterson, S., 1990. Feature-Oriented Domain Analysis Feasibility Study (FODA). Tech. Rep. CMU/SEI-90-TR-021, Carnegie Mellon University, Software Engineering Institute, Pittsburgh, PA.
49. Kiziltan Z., Hnich B. Symmetry breaking in a rack configuration problem. Seventeenth International Joint Conference on Artificial Intelligence (IJCAI-2001), Workshop on Modelling and Solving Problems with Constraints. Seattle, WA 2001, 1-6.
50. Leitner G., Felfernig A., Blazek P., Reinfrank F., Ninaus G. User interfaces for configuration environments. Knowledge-based Configuration - From Research to Business Cases 2014, 89-106. Morgan Kaufmann Publishers, Waltham, MA, (Chapter 8). A. Felfernig, L. Hotz, C. Bagley, J. Tiihonen (Eds.).
51. Li B., Chen L., Huang Z., Zhong Y. Product configuration optimization using a multiobjective genetic algorithm. International Journal of Advanced Manufacturing Technology 2006, 30(1-2):20-29.
52. Mackworth A. Consistency in networks of relations. Artificial Intelligence 1977, 8(1):99-118.
53. Mailharro D. A classification and constraint-based framework for configuration. Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AI EDAM) 1998, 12(4):383-397.
54. McDermott J. R1: a rule-based configurer of computer systems. Artificial Intelligence 1982, 19(1):39-88.
55. McGuinness D., Wright J. An industrial-strength description logic-based configurator platform. Intelligent Systems and their Applications, IEEE 1998, 13(4):69-77.
56. Mittal S., Falkenhainer B. Dynamic constraint satisfaction problems. Proceedings of the eighth national conference on artificial intelligence (AAAI-90). Boston, MA 1990, 25-32. Aug.
57. Mittal S., Frayman F. Towards a generic model of configuration tasks. 11th International Joint Conference on Artificial Intelligence (IJCAI-89). Detroit, Michigan 1989, vol. 2:1395-1401.
58. Neumann B. Configuration expert systems: a case study and tutorial. Proc. 1988 SGAICO Conference on Artificial Intelligence in Manufacturing, Assembly, and Robotics. Oldenbourg, Munich 1988, 27-68. H.O. Bunke (Ed.).
59. Pinedo M. Scheduling: Theory, Algorithms, and Systems 2012, Springer, New York, NY. fourth ed.
60. Pitiot P., Aldanondo M., Vareilles E., Gaborit P., Djefel M.S.C. Concurrent product configuration and process planning, towards an approach combining interactivity and optimality. International Journal of Production Research 2013, 51(2):524-541.
61. Puget J.-F., Albert P. PECOS: programmation par contraintes orientée objets. Génie logiciel et systèmes experts (GLSE) 1991, 23:100-105.
62. Reiter R. A theory of diagnosis from first principles. Artificial Intelligence 1987, 32(1):57-95.
63. Handbook of Constraint Programming. Foundations of Artificial Intelligence 2006, Elsevier, New York, NY. F. Rossi, P. vanBeek, T. Walsh (Eds.).
64. Russel S., Norvig P. Artificial Intelligence - A Modern Approach 2003, Prentice Hall, Upper Saddle River, NJ. 2nd Edition.
65. Sabin D., Weigel R. Product configuration frameworks - a survey. IEEE Intelligent Systems 1998, 13(4):42-49.
66. Schröder C., Möller R., Lutz C. A partial logical reconstruction of PLAKON/KONWERK. Proceedings of the Workshop on Knowledge Representation and Configuration WRKP'96. No. D-96-04 in DFKI Documents 1996, 55-64. F. Baader, H.-J. Bürckert, A. Günther, W. Nutt (Eds.).
67. Sinz, C., Haag, A., Narodytska, N., Walsh, T., Gelle, E., Sabin, M., Junker, U., O'Sullivan, B., Rabiser, R., Dhungana, D., Grünbacher, P., Lehner, K., Federspiel, C., Naus, D., 2007. Configuration. IEEE Intelligent Systems 22 (1), 78-90.
68. Soininen T., Tiihonen J., Männistö T., Sulonen R. Towards a general ontology of configuration. Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AI EDAM) 1998, 12(4):357-372.
69. Soininen, T., Niemelä, I., Tiihonen, J., Sulonen, R., 2001. Representing configuration knowledge with weight constraint rules. In: Provetti, A., Son, T.C. (Eds.), 1st International Workshop on Answer Set Programming: Towards Efficient and Scalable Knowledge (AAAI Technical, Report SS-01-01). pp. 195-201.
70. Soloway E., Bachant J., Jensen K. Assessing the maintainability of XCON-in-RIME: coping with the problem of very large rule-bases. Proceedings of the Sixth National Conference on Artificial Intelligence (AAAI-87). Seattle, Washington 1987, 824-829. July 13-17.
71. Stumptner M. An overview of knowledge-based configuration. AI Communications 1997, 10(2):111-126.
72. Stumptner M., Friedrich G., Haselböck A. Generative constraint-based configuration of large technical systems. Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AI EDAM) 1998, 12(4):307-320.
73. Terashima-Marin H., Ross P., Valenzuela-Rendon M. Hyper-heuristics for the dynamic variable ordering in constraint satisfaction problems. Genetic and Evolutionary Computation Conference (GECCO'08). Atlanta, Georgia 2008, 571-578.
74. Tiihonen J., Soininen T., Niemelä I., Sulonen R. A practical tool for mass-customising configurable products. Proceedings of the 14th International Conference on Engineering Design, Stockholm, Sweden, August 19-21, 2003, CDROM 2003, p. 10 (Paper number: 1290).
75. Tiihonen J., Heiskala M., Anderson A., Soininen T. WeCoTin - A practical logic-based sales configurator. AI Communications 2013, 26(1):99-131.
76. Tsang E. Foundations of Constraint Satisfaction 1993, Academic Press, London, San Diego, New York.
77. Warmer J., Kleppe A. The Object Constraint Language: Getting Your Models Ready for MDA 2003, Addison-Wesley Longman Publishing, Boston, MA. second ed.