Logical foundations of artificial intelligence
Logical foundations of artificial intelligence
Structural complexity 1
Completeness in approximation classes
Information and Computation
Introduction to the theory of complexity
Introduction to the theory of complexity
Randomized algorithms
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties
The Approximability of Constraint Satisfaction Problems
SIAM Journal on Computing
Constraint Satisfaction: The Approximability of Minimization Problems
CCC '97 Proceedings of the 12th Annual IEEE Conference on Computational Complexity
The complexity of satisfiability problems
STOC '78 Proceedings of the tenth annual ACM symposium on Theory of computing
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
A Soft Constraint of Equality: Complexity and Approximability
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
Finding diverse and similar solutions in constraint programming
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Reasoning about optimal collections of solutions
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Parameterized complexity and kernelizability of max ones and exact ones problems
MFCS'10 Proceedings of the 35th international conference on Mathematical foundations of computer science
Algorithms for max hamming exact satisfiability
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
On the hardness of losing weight
ACM Transactions on Algorithms (TALG)
Algorithms for the maximum hamming distance problem
CSCLP'04 Proceedings of the 2004 joint ERCIM/CoLOGNET international conference on Recent Advances in Constraints
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In this paper we consider a new optimization problem, called MAX HAMMINGDISTANCE(F) where F is a family of Boolean constraints. This problem consists in finding two satisfying assignments that differ in the maximum number of variable values: in other words, the problem looks for the maximum difference between two models of the constraints given in input. We give a complete classification of the approximability properties of MAX HAMMINGDISTANCE(F) by using a specialization of the criteria introduced by Schaefer in order to classify constraint satisfaction problems and subsequently used by Khanna, Sudan, Trevisan, and Williamson to classify constraint satisfaction optimization problems.