Efficient and friendly environment for computational intelligence

There are many knowledge-based data mining frameworks and it is common to think that new ones can not come up with anything new. This article refutes such claims. We propose a sophisticated unification mechanism and two-tier machine cache system aimed at saving time and memory. No machine is run twice. Instead, machines are reused wherever they are repeatedly requested (regardless of request context). These mechanisms are integrated with hierarchical task scheduler. Its unique design facilitates efficient automatic management of large numbers of tasks with natural adjustment to available computational resources. The system is also equipped with extremely powerful and general module for analysis of learning processes and evaluation of machine configurations with huge bunch of testing procedures of different kinds. Uniform results collection and query system is independent from particular learning machines. All the solutions are possible thanks to very general and universal definition of machine, configuration, machine context, machine information exchange and other necessary concepts. The ideas presented here, have been implemented and tested.