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Games are among problems that can be reduced to optimization, for which one of the most universal and productive solving method is a heuristic approach. In this article we present results of benchmark tests on using 5 heuristic methods to solve a physical model of the darts game. Discussion of the scores and conclusions from the research have shown that application of heuristic methods can simulate...
In this paper, the idea of applying some hybrid genetic algorithms with gradient local search and evolutionary optimization techniques is formulated. For two different test functions the proposed versions of the algorithms have been examined. Research results are presented and discussed to show potential efficiency in optimization purposes.
The data-driven task parallelism execution model can support parallel programming models that are well suited for large-scale distributed-memory parallel computing, for example, simulations and analysis pipelines running on clusters and clouds. We describe a novel compiler intermediate representation and optimizations for this execution model, including adaptions of standard techniques alongside novel...
We seek to enable efficient large-scale parallel execution of applications in which a shared filesystem abstraction is used to couple many tasks. Such parallel scripting (many-task computing, MTC) applications suffer poor performance and utilization on large parallel computers because of the volume of filesystem I/O and a lack of appropriate optimizations in the shared filesystem. Thus, we design...
Combining pattern recognition is the promising direction in designing an effective classifier systems. There are several approaches of collective decision-making, among them voting methods, where the decision is a combination of individual classifiers' outputs are quite popular. This article focuses on the problem of fuser design which uses continuous outputs of individual classifiers to make a decision...
Combining classifiers are nowadays one of the most promising direction in pattern recognition. There are many methods of decision making which could be used by the ensemble of classifiers. The most popular are methods that have their origin in voting, where the decision of the common classifier is a combination of individual classifiers' outputs, i.e. classifiers' responses (class numbers) or values...
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