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Although participants may make additional mental tours and estimate their costs before actually providing a new solution to the experimenter, it is clear that human problem-solving is taking very efficient shortcuts in solving the TSP, perhaps by exploiting deep structures of the problem.
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Such algorithms must exploit domain-specific structures of the problems being considered.
Learners need to recognize the deep structure of the problem before they can connect current problems with structurally similar prior problems.
In order to do so, we carefully exploit the underlying structure of the problem.
We exploit this structure of the problem for its solution.
This method preserves the geometric structure of the problem.
In more general settings, the closeness of the approximation to the optimal solution depends on the structure of the problem.
Based on the natural symplectic structure, the non-canonical Hamiltonian structure of the problem is derived.
The first we've encountered already, which is that many more situations have the structure of the problem of the commons than one might antecedently realize.
An analytical solution approach is proposed based on the structure of the problem.
In this work we propose a different approach, exploiting the rich geometrical structure of the problem.
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CEO of Professional Science Editing for Scientists @ prosciediting.com