Piero Scaruffi

These are excerpts and elaborations from my book "The Nature of Consciousness"

Programs That Learn: Deduction The analytic paradigm, instead, utilizes past problem solving experience to formulate the search strategy in the space of potential solutions. Deductive learning systems include Paul Rosenbloom's "chunking", Jerry DeJong's "explanation-based learning", Jaime Carbonell's "derivational analogy", John Holland's "classifiers". Rosenbloom’s programs are aimed at simulating the law of practice: the time required to perform an action decreases exponentially with the number of times the action is performed. His “chunking” technique progressively reduces the amount of processing needed to determine what action must be taken in the face of a situation. Ultimately, it tends to reduce every situation-action pair to a  stimulus-response pair that does not require any “thinking” at all. An explanation-based learning system (inspired by Richard Fikes' work) is given a high-level description of the target concept, a single positive instance of the concept, a description of what a concept definition is and domain knowledge.  The system generates a proof that the positive instance satisfies the target concept and then generalizes the proof.  Learning by analogy was originally investigated by Patrick Winston, who focused on learning a concept analogous to another concept (which resulted in a transfer of features from a frame to another frame). Carbonell applied the method to sequences of operators rather than to features. Derivational analogy solves a problem by tweaking a plan (represented as a hierarchical goal structure) used to solve a previous problem.   Back to the beginning of the chapter "Machine Intelligence" | Back to the index of all chapters