Sentence examples for states of the problem from inspiring English sources

The basic idea behind computational heuristics is that rules can be identified that serve as guidelines for finding a solution to a given problem quickly and efficiently by avoiding undesired states of the problem space.

The capacity developing describes the learning ability of an algorithm to adaptively change its parameters, structures, and/or its learning potential according to the search states of the problem to be solved.

In our case, this structure is a binary tree where nodes are valid states of the problem (partial and full configurations) and edges represent individual selection/deselection of features.

Recent papers show its excellent performance when tested on state-of-the-art problems.

Despite the relevance of the problem, state-of-the-art management solutions for grid systems usually neglect the identification and handling of failures at runtime.

The state-of-the-art image registration problem can be expressed in the following way.

The results are compared with 11 state-of-the-art algorithms for constrained problems and 6 state-of-the-art algorithms for unconstrained problems.

Tables 1– 3 summarize the current state-of-the-art for these three problems.

Each configuration is a "state" of the problem space.

The model is customized to the primarily compressive stress state of the problem at hand and is calibrated to the compressive hysteresis of the material.

More importantly, the physical configuration of the problem changed in the high interactivity condition: thus, participants' actions wrought changes in the physical configuration of the problem, changes that are contingent on the preceding state of the problem.