Download Autonomous Search by Youssef Hamadi, Eric Monfroy, Frédéric Saubion (auth.), PDF

By Youssef Hamadi, Eric Monfroy, Frédéric Saubion (auth.), Youssef Hamadi, Eric Monfroy, Frédéric Saubion (eds.)

Decades of strategies in combinatorial challenge fixing have produced greater and extra advanced algorithms. those new tools are larger on account that they could remedy greater difficulties and handle new software domain names. also they are extra complicated which means they're demanding to breed and sometimes tougher to fine-tune to the peculiarities of a given challenge. This final element has created a paradox the place effective instruments are out of succeed in of practitioners.

Autonomous seek (AS) represents a brand new study box outlined to exactly tackle the above problem. Its significant energy and originality consist within the incontrovertible fact that challenge solvers can now practice self-improvement operations in accordance with research of the performances of the fixing approach -- together with non permanent reactive reconfiguration and long term development via self-analysis of the functionality, offline tuning and on-line keep watch over, and adaptive keep an eye on and supervised keep watch over. self sustaining seek "crosses the chasm" and gives engineers and practitioners with platforms which are in a position to autonomously self-tune their functionality whereas successfully fixing difficulties.

This is the 1st e-book devoted to this subject, and it may be used as a reference for researchers, engineers, and postgraduates within the components of constraint programming, desktop studying, evolutionary computing, and suggestions regulate concept. After the editors' advent to independent seek, the chapters are excited by tuning set of rules parameters, independent entire (tree-based) constraint solvers, self sufficient regulate in metaheuristics and heuristics, and destiny self sufficient fixing paradigms.

Autonomous seek (AS) represents a brand new examine box outlined to exactly tackle the above problem. Its significant energy and originality consist within the proven fact that challenge solvers can now practice self-improvement operations in line with research of the performances of the fixing technique -- together with temporary reactive reconfiguration and long term development via self-analysis of the functionality, offline tuning and on-line regulate, and adaptive regulate and supervised keep an eye on. self sufficient seek "crosses the chasm" and gives engineers and practitioners with platforms which are capable of autonomously self-tune their functionality whereas successfully fixing difficulties.

This is the 1st e-book devoted to this subject, and it may be used as a reference for researchers, engineers, and postgraduates within the components of constraint programming, desktop studying, evolutionary computing, and suggestions regulate thought. After the editors' creation to self sufficient seek, the chapters are fascinated by tuning set of rules parameters, independent entire (tree-based) constraint solvers, self reliant keep watch over in metaheuristics and heuristics, and destiny self sufficient fixing paradigms.

This is the 1st publication devoted to this subject, and it may be used as a reference for researchers, engineers, and postgraduates within the parts of constraint programming, computing device studying, evolutionary computing, and suggestions keep an eye on thought. After the editors' advent to independent seek, the chapters are excited by tuning set of rules parameters, self sufficient whole (tree-based) constraint solvers, self sufficient regulate in metaheuristics and heuristics, and destiny self sufficient fixing paradigms.

This is the 1st publication devoted to this subject, and it may be used as a reference for researchers, engineers, and postgraduates within the components of constraint programming, desktop studying, evolutionary computing, and suggestions keep an eye on idea. After the editors' creation to self sustaining seek, the chapters are fascinated by tuning set of rules parameters, independent whole (tree-based) constraint solvers, independent regulate in metaheuristics and heuristics, and destiny independent fixing paradigms.

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1 The problem of parameter tuning can then be seen as a search problem S, u in the parameter space 1 Observe that due to the possible presence of sub-parameters the number of quantitative parameters n depends on the instantiations of q1 , . . qm . This makes the notation somewhat inaccurate, but we use it for sake of simplicity. 20 A. E. Eiben and S. K. Smit Fig. 2). , the evolutionary algorithm instance using the values of p, ¯ on the given problem instance(s). Solutions of the parameter tuning problem can then be defined as parameter vectors with maximum utility.

More tests can improve (sharpen) the stability of the expected utility to a level such that the superiority of one vector over another can be safely concluded, but more tests come with a price of longer runtime. The methods in this group use the same trick to deal with this problem: performing only a few tests per parameter vector initially and increasing this number to the minimum level that is enough to obtain statistically sound comparisons between the given parameter vectors. Such methods are known as statistical screening, ranking, and selection.

In the first method, the quantitative (numerical) parameters are represented by a vector and are evolved using a meta-(1+λ ) ES. At each generation, a set of λ new vectors is created using a Gaussian distribution centered at the current best vector. Racing is then used to determine which vector has the highest utility. By using racing, not all of the λ individuals have to be evaluated B times to determine the current best vector. It is expected that many of the vectors are eliminated after just a few tests saving a large portion of computational resources.

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