Hard constraint satisfaction problems have hard gaps at location 1
نویسندگان
چکیده
منابع مشابه
Hard constraint satisfaction problems have hard gaps at location 1
An instance of Max CSP is a finite collection of constraints on a set of variables, and the goal is to assign values to the variables that maximises the number of satisfied constraints. Max CSP captures many well-known problems (such as Max k-SAT and Max Cut) and is consequently NP-hard. Thus, it is natural to study how restrictions on the allowed constraint types (or constraint languages) affe...
متن کاملHard constraint satisfaction problems have hard gaps at location 1 1
An instance of the maximum constraint satisfaction problem (Max CSP) is a nite collection of constraints on a set of variables, and the goal is to assign values to the variables that maximises the number of satis ed constraints. Max CSP captures many well-known problems (such as Max k-SAT and Max Cut) and is consequently NP-hard. Thus, it is natural to study how restrictions on the allowed cons...
متن کاملModelling Exceptionally Hard Constraint Satisfaction Problems
Randomly-generated constraint satisfaction problems go through a phase transition as the constraint tightness varies. Loose constraints give an `easy-soluble' region, where problems have many solutions and are almost always easy to solve. However, in this region, systematic search algorithms may occasionally encounter problems which are extremely expensive to solve. It has been suggested that i...
متن کاملValued Constraint Satisfaction Problems: Hard and Easy Problems
In order to deal with over-constrained Constraint Satisfaction Problems, various extensions of the CSP framework have been considered by taking into account costs, uncertainties, preferences, priorities...Each extension uses a specific mathematical operator (+;max : : :) to aggregate constraint violations. In this paper, we consider a simple algebraic framework, related to Partial Constraint Sa...
متن کاملGA-easy and GA-hard Constraint Satisfaction Problems
In this paper we discuss the possibilities of applying genetic algorithms (GA) for solving constraint satisfaction problems (CSP). We point out how the greediness of deterministic classical CSP solving techniques can be counterbalanced by the random mechanisms of GAs. We tested our ideas by running experiments on four diierent CSPs: N-queens, graph 3-colouring, the traac lights and the Zebra pr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Theoretical Computer Science
سال: 2009
ISSN: 0304-3975
DOI: 10.1016/j.tcs.2009.05.022