Finding Interesting Things: Population-based Adaptive Parameter Sweeping
نویسندگان
چکیده
Modeland simulation-designers are often interested not in the optimum output of their system, but in understanding how the output is sensitive to different parameters. This can require an inefficient sweep of a multidimensional parameter space, with many samples tested in regions of the space where the output is essentially all the same, or a sparse sweep which misses crucial “interesting” regions where the output is strongly sensitive. In this paper we introduce a novel population-oriented approach to adaptive parameter sweeping which focuses its samples on these sensitive areas. The method is easy to implement and model-free, and does not require any previous knowledge about the space. In a weakened form the method can operate in non-metric spaces such as the space of genetic program trees. We demonstrate the method on three test problems, showing that it identifies regions of the space where the slope of the output is highest, and concentrates samples on those regions.
منابع مشابه
Adaptive Search for Interesting Things
The results of a parameter sweep over a multidimensional parameter space are often used to gain an understanding of the space beyond simply identifying optima. But sweeps are costly, and so it is highly desirable to adaptively sample the space in such a way as to concentrate precious samples on the more “interesting” areas of the space. In this paper we analyze and expand on a previous work whi...
متن کاملAdaptive Tuning of Model Predictive Control Parameters based on Analytical Results
In dealing with model predictive controllers (MPC), controller tuning is a key design step. Various tuning methods are proposed in the literature which can be categorized as heuristic, numerical and analytical methods. Among the available tuning methods, analytical approaches are more interesting and useful. This paper is based on a proposed analytical MPC tuning approach for plants can be appr...
متن کاملParameter Sweeping Programming Model in Aneka on Data Mining Applications
Data mining applications and techniques are used in many areas as a required knowledge discovery from large data sets. Cloud computing is one of the prevailing models based on IP architecture. Cloud computing is nothing but the delivery of the computing services over the internet to improve the business of many organizations. Cloud systems which can be effectively handle parallel mining since t...
متن کاملSLA-aware Interactive Workflow Assistant for HPC Parameter Sweeping Experiments
A common workflow in science and engineering is to (i) setup and deploy large experiments with tasks comprising an application and multiple parameter values; (ii) generate intermediate results; (iii) analyze them; and (iv) reprioritize the tasks. These steps are repeated until the desired goal is achieved, which can be the evaluation/simulation of complex systems or model calibration. Due to ti...
متن کاملEquidistribution grids for two-parameter convection–diffusion boundary-value problems
In this article, we propose an adaptive grid based on mesh equidistribution principle for two-parameter convection-diffusion boundary value problems with continuous and discontinuous data. A numerical algorithm based on an upwind finite difference operator and an appropriate adaptive grid is constructed. Truncation errors are derived for both continuous and discontinuous problems. Parameter uni...
متن کامل