Years and Authors of Summarized Original Work
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2013(1); Bei, Chen, Zhang
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2013(2); Bei, Chen, Zhang
Problem Definition
This problem investigates the effect of the lack of input information on computational hardness. The central question under investigation is the following:
How much extra difficulty is introduced due to the lack of input knowledge?
We explore this question by studying search problems. Suppose that on an input instance x, there is a set S(x) of solutions. A search problem is to find a solution s ∈ S(x) for the input x. More specifically, we consider the fairly broad class of Constraint Satisfaction Problems (CSPs): Suppose that there is an input space {0, 1}n and a space Ω = { 0, 1}m of candidate solutions. The problem is defined by a number of constraints \(C_{1},C_{2},\ldots ,C_{m}(,\ldots )\), where each C i : { 0, 1}n+m → { 0, 1} is a 0-1 function on the input and solution variables. The valid solutions for input x are defined as those s that satisfy all constraints C
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Bei, X., Chen, N., Zhang, S. (2016). Trial and Error Algorithms. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_789
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DOI: https://doi.org/10.1007/978-1-4939-2864-4_789
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