Abstract: A method for facilitating an optimization of a control space in n dimensions is provided. The control space includes a plurality of points, and the method includes removing at least one hyperplane of the control space, and perturbing the remaining points of the control space to lessen errors relative to the control space prior to the removal of at least one hyperplane.

Abstract: In an experimental design strategy for evaluating systems with complex physical, chemical and structural requirements, a first population of entities is synthesized, a property of each of the entities can be detected by a high throughput screening (HTS) method and a genetic algorithm based on the property of the entities is executed to identify a second population of entities. A system for screening constructs to determine a problem solution includes a generator to provide a binary string representing a random first population of the constructs, a combinatorial reactor to synthesize the first population of constructs and to determine a fitness function for each construct of the population by a high throughput screening process and an executor to execute a genetic algorithm on the first population to produce a generation that defines a second population of the materials.

Abstract: A method for facilitating an optimization of a control space in n dimensions is provided. The control space includes a plurality of points, and the method includes removing at least one hyperplane of the control space, and perturbing the remaining points of the control space to lessen errors relative to the control space prior to the removal of at least one hyperplane.

Abstract: A hybrid learning system is provided for searching an experimental space. A data mart is configured to acquire, store, and manipulate a set or meta-set of data including at least historical experimental data, descriptor data, and concurrent experimental data. A search engine is designed to use unsupervised learning techniques to select a set of evaluation points representing a corresponding set of experiments to be run, based on data from the data mart. A point evaluation mechanism provided with supervised learning modules which perform predictive processing based on the evaluation points selected by the search engine, and a scoring module performs a rating operation on outputs of the learning modules to rate the outputs of the learning modules from best to worst. The data mart search engine and point evaluation mechanism allow for a repetitive processing to refine an output of potential solutions without the requirement of continually running actual physical experiments.