Conflict Detection and Diagnosis in Configuration

The widespread industrial application of configuration technologies triggers an increasing demand for intelligent techniques that efficiently support anomaly management operations for configuration knowledge bases. Examples of such operations are the testing and debugging of faulty knowledge bases (see Chapter 11) and the detection of redundancies in configuration knowledge bases (see Chapter 12). The goal of this chapter is to discuss techniques and algorithms that form the technological basis for the aforementioned anomaly management operations.

[1]  Alexander Felfernig,et al.  Redundancy Detection in Configuration Knowledge , 2014 .

[2]  Felix Naumann,et al.  Data fusion , 2009, CSUR.

[3]  Markus Stumptner,et al.  Knowledge Engineering for Configuration Systems , 2014 .

[4]  Alexander Felfernig,et al.  An efficient diagnosis algorithm for inconsistent constraint sets , 2011, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[5]  Amir Fijany,et al.  New approaches for efficient solution of hitting set problem , 2004 .

[6]  Alexander Felfernig,et al.  CoreDiag: Eliminating Redundancy in Constraint Sets , 2011 .

[7]  Alexander Felfernig,et al.  FastXplain: Conflict Detection for Constraint-Based Recommendation Problems , 2010, IEA/AIE.

[8]  Markus Stumptner,et al.  Configuration Knowledge Representation and Reasoning , 2014 .

[9]  Ulrich Junker,et al.  QUICKXPLAIN: Preferred Explanations and Relaxations for Over-Constrained Problems , 2004, AAAI.

[10]  VARUN CHANDOLA,et al.  Anomaly detection: A survey , 2009, CSUR.

[11]  D. Jannach,et al.  Finding Preferred Query Relaxations in Content-based Recommenders , 2006, 2006 3rd International IEEE Conference Intelligent Systems.

[12]  Virginia E. Barker,et al.  Expert systems for configuration at Digital: XCON and beyond , 1989, Commun. ACM.

[13]  Alexander Felfernig,et al.  Bfx: Diagnosing Conflicting Requirements in Constraint-Based Recommendation , 2011, Int. J. Artif. Intell. Tools.

[14]  Markus Stumptner,et al.  Consistency-based diagnosis of configuration knowledge bases , 1999, Artif. Intell..

[15]  Alexander Felfernig,et al.  Knowledge-Based Configuration: From Research to Business Cases , 2014 .

[16]  Alexander Felfernig,et al.  Automated repair of scoring rules in constraint-based recommender systems , 2013, AI Commun..

[17]  Raymond Reiter,et al.  A Theory of Diagnosis from First Principles , 1986, Artif. Intell..

[18]  Markus Stumptner,et al.  Configuring Large Systems Using Generative Constraint Satisfaction , 1998, IEEE Intell. Syst..