Computer implemented machine learning method and system

Details Computer implemented machine learning method and system Computer implemented machine learning method and system

1996-07-12

1998-11-24

Downs, Robert W.

G06F 1518

Patent

active

058419470

ABSTRACT:
One or more machine code entities such as functions are created which represent solutions to a problem and are directly executable by a computer. The programs are created and altered by a program in a higher level language such as "C" which is not directly executable, but requires translation into executable machine code through compilation, interpretation, translation, etc. The entities are initially created as an integer array that can be altered by the program as data, and are executed by the program by recasting a pointer to the array as a function type. The entities are evaluated by executing them with training data as inputs, and calculating fitnesses based on a predetermined criterion. The entities are then altered based on their fitnesses using a machine learning algorithm by recasting the pointer to the array as a data (e.g. integer) type. This process is iteratively repeated until an end criterion is reached. The entities evolve in such a manner as to improve their fitness, and one entity is ultimately produced which represents an optimal solution to the problem. Each entity includes a plurality of directly executable machine code instructions, a header, a footer, and a return instruction. The alteration process is controlled such that only valid instructions are produced. The headers, footers and return instructions are protected from alteration. The system can be implemented on an integrated circuit chip, with the entities stored in high speed memory in a central processing unit.

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