Intelligent Tree Computing, Decision Trees and Soft OOP Tree Computing

Cyrus F. Nourani

Intelligent tree computing techniques are defined with applications to decision tree computing defining decisive agent computing. New linguistics abstraction theories are presented. Treating objects as abstract data types and a two level programming approach to OOP allows us to define Pullup abstractions to treat incompatible objects. A basis for a tree computing theory for abstract objects with intelligent languages and intelligent algebraic tree rewriting is presented. The formulation leads to theoretical results that provide the basis for parallel algebraic tree rewrite computing with intelligent trees. Tree completion theorems are presented, and techniques for generating initial intelligent models are developed. We also have soundness and completeness theorems for the algebraic tree computing theory for abstract objects and its preliminary model theory. New frontiers for object level computing with tree rewriting is presented.

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