The present invention relates, generally, to a system and process for readily determining, for a specified knowledge domain in a given field of endeavor as represented in a neural network, perturbations applicable to such specified knowledge domain that will produce a desired output, and employs neural network-based technology to quickly and easily arrive at a determination of the particular perturbation-output mapping relationship associated with or required to produce the desired output. Typically, such system and process can be utilized to determine those input patterns to a neural network, which input patterns may be representative of designs, concepts, or plans of action, that will produce a desired result within the particular knowledge domain, and operates to determine the particular input-output mapping relationship associated with or required to produce the desired result. Such system can be employed in some instances and in some embodiments as a target seeking system for use with various design or problem solving applications, and can, in some embodiments, also comprise or be comprised of a system and process for autonomously producing and identifying desirable design concepts.
Prior to this invention, artificial neural network (ANN) emulations of biological systems were used for tasks such as pattern recognition, neural control, and the generalization of experimental data. The present system represents a new approach and a new application of ANN's in which the system functions to permit a user to specify desired outputs or results for a given design or problem solving application and to thereafter obtain identification of system perturbations that would produce the desired output. Such system perturbations may be external to the ANN (e.g., changes to the ANN data inputs) or internal to the ANN (e.g., changes to weights, biases, etc.) By utilizing neural network-based technology, such identification of required perturbations can be achieved easily, quickly, and, if desired, autonomously.