Climent L, Salido M, Barber F (2011) Reformulating dynamic linear constraint satisfaction problems as weighted csps for searching robust solutions. In: Ninth symposium of abstraction, reformulation, and approximation (SARA-11), pp 34–41
Dechter R, Dechter A (1988) Belief maintenance in dynamic constraint networks. In: Proceedings of the 7th national conference on, artificial intelligence (AAAI-88), pp 37–42
Dechter R, Meiri I, Pearl J (1991) Temporal constraint networks. Artif Intell 49(1):61–95
[+]
Climent L, Salido M, Barber F (2011) Reformulating dynamic linear constraint satisfaction problems as weighted csps for searching robust solutions. In: Ninth symposium of abstraction, reformulation, and approximation (SARA-11), pp 34–41
Dechter R, Dechter A (1988) Belief maintenance in dynamic constraint networks. In: Proceedings of the 7th national conference on, artificial intelligence (AAAI-88), pp 37–42
Dechter R, Meiri I, Pearl J (1991) Temporal constraint networks. Artif Intell 49(1):61–95
Fargier H, Lang J (1993) Uncertainty in constraint satisfaction problems: a probabilistic approach. In: Proceedings of the symbolic and quantitative approaches to reasoning and uncertainty (EC-SQARU-93), pp 97–104
Fargier H, Lang J, Schiex T (1996) Mixed constraint satisfaction: a framework for decision problems under incomplete knowledge. In: Proceedings of the 13th national conference on, artificial intelligence, pp 175–180
Fowler D, Brown K (2000) Branching constraint satisfaction problems for solutions robust under likely changes. In: Proceedings of the international conference on principles and practice of constraint programming (CP-2000), pp 500–504
Goles E, Martínez S (1990) Neural and automata networks: dynamical behavior and applications. Kluwer Academic Publishers, Dordrecht
Hays W (1973) Statistics for the social sciences, vol 410, 2nd edn. Holt, Rinehart and Winston, New York
Hebrard E (2006) Robust solutions for constraint satisfaction and optimisation under uncertainty. PhD thesis, University of New South Wales
Herrmann H, Schneider C, Moreira A, Andrade Jr J, Havlin S (2011) Onion-like network topology enhances robustness against malicious attacks. J Stat Mech Theory Exp 2011(1):P01,027
Larrosa J, Schiex T (2004) Solving weighted CSP by maintaining arc consistency. Artif Intell 159:1–26
Larrosa J, Meseguer P, Schiex T (1999) Maintaining reversible DAC for Max-CSP. J Artif Intell 107(1):149–163
Mackworth A (1977) On reading sketch maps. In: Proceedings of IJCAI’77, pp 598–606
Sam J (1995) Constraint consistency techniques for continuous domains. These de doctorat, École polytechnique fédérale de Lausanne
Schiex T, Fargier H, Verfaillie G (1995) Valued constraint satisfaction problems: hard and easy problems. In: Proceedings of the 14th international joint conference on, artificial intelligence (IJCAI-95), pp 631–637
Taillard E (1993) Benchmarks for basic scheduling problems. Eur J Oper Res 64(2):278–285
Verfaillie G, Jussien N (2005) Constraint solving in uncertain and dynamic environments: a survey. Constraints 10(3):253–281
Wallace R, Freuder E (1998) Stable solutions for dynamic constraint satisfaction problems. In: Proceedings of the 4th international conference on principles and practice of constraint programming (CP-98), pp 447–461
Wallace RJ, Grimes D (2010) Problem-structure versus solution-based methods for solving dynamic constraint satisfaction problems. In: Proceedings of the 22nd international conference on tools with artificial intelligence (ICTAI-10), IEEE
Walsh T (2002) Stochastic constraint programming. In: Proceedings of the 15th European conference on, artificial intelligence (ECAI-02), pp 111–115
William F (2006) Topology and its applications. Wiley, New York
Winer B (1971) Statistical principles in experimental design, 2nd edn. McGraw-Hill, New York
Yorke-Smith N, Gervet C (2009) Certainty closure: reliable constraint reasoning with incomplete or erroneous data. J ACM Trans Comput Log (TOCL) 10(1):3
[-]