A composition of autonomous self-learning skill software components interact with one another to solve a real time complex task. Each software component includes a knowledge base and an inference algorithm that uses the knowledge base to solve a given data-processing task involving input data. Each software component may also include a machine learning algorithm for training the knowledge base with new data in real-time as the new data is received.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer system, comprising: at least one processor; memory associated with the at least one processor; and a program supported in the memory, the program containing a plurality of instructions executable by the at least one processor, comprising a composition of autonomous self-learning skill software components, each software component including a knowledge base and an inference algorithm that uses the knowledge base to solve a given data-processing task involving input data, each software component also including a machine learning algorithm for training the knowledge base with new data in real-time as the new data is received, wherein the software components interact with one another to solve a complex task. 2. The system of claim 1, wherein the inference algorithm is an artificial intelligence algorithm. 3. The system of claim 1, wherein the knowledge base comprises rules, fuzzy rules, Bayesian networks, neural networks, neurofuzzy networks, support vector machines, statistical model equations, dynamic model equations, mathematical transformations, or source code calculation routines. 4. The system of claim 1, wherein the machine learning algorithm is an artificial intelligence algorithm. 5. The system of claim 1, wherein the machine learning algorithm includes an inductive learning capability. 6. The system of claim 1, wherein each software component includes a specification of problem states for which it is applicable. 7. The system of claim 1, wherein each software component filters the results of a data-processing task. 8. The system of claim 7, wherein the results are filtered to verify that they are within allowed operating boundaries. 9. The system of claim 1, wherein software components of the same type share the same inference algorithm and the same or different machine learning algorithm. 10. The system of claim 9, wherein the software components of the same type have different knowledge bases or different specifications of states of the problem. 11. The system of claim 1, wherein at least one of the software components comprises an optimization skill that provides an optimization recommendation, an identification model skill that predicts new values of variables under given a situation or hypothesis, a diagnosis skill that identifies causes of failures, a failure prediction skill that predicts possible failures or their likelihood, a soft sensor skill that estimates hidden or error data based on available data, a composed model skill that generates outputs based on multiple complementary models, or a filtering skill. 12. A computer program product residing on a non-transitory computer readable medium including a skill composition program containing a plurality of instructions executable by one or more computer processors, including: a plurality of autonomous self-learning skill software components, each software component including a knowledge base and an inference algorithm that uses the knowledge base to solve a given data-processing task involving input data, each software component also including a machine learning algorithm for training the knowledge base with new data in real-time as the new data is received, wherein the software components interact with one another to solve a complex task. 13. The computer program product of claim 12, wherein the inference algorithm is an artificial intelligence algorithm. 14. The computer program product of claim 12, wherein the knowledge base comprises rules, fuzzy rules, Bayesian networks, neural networks, neurofuzzy networks, support vector machines, statistical model equations, dynamic model equations, mathematical transformations, or source code calculation routines. 15. The computer program product of claim 12, wherein the machine learning algorithm is an artificial intelligence algorithm. 16. The computer program product of claim 12, wherein the machine learning algorithm includes an inductive learning capability. 17. The computer program product of claim 12, wherein each software component includes a specification of states of the problem for which it is applicable. 18. The computer program product of claim 12, wherein each software component filters the results of a data-processing task. 19. The computer program product of claim 18, wherein the results are filtered to verify that they are within allowed operating boundaries. 20. The computer program product of claim 12, wherein software components of the same type share the same inference algorithm and the same or different machine learning algorithm. 21. The computer program product of claim 20, wherein the software components of the same type have different knowledge bases or different specifications of states of the problem. 22. The computer program product of claim 12, wherein at least one of the software components comprises an optimization skill that provides an optimization recommendation, an identification model skill that predicts new values of variables under given a situation or hypothesis, a diagnosis skill that identifies causes of failures, a failure prediction skill that predicts possible failures or their likelihood, a soft sensor skill that estimates hidden or error data based on available data, a composed model skill that generates outputs based on multiple complementary models, or a filtering skill.