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Methods for Integrating Knowledge with the Three-Weight Optimization Algorithm for Hybrid Cognitive Processing

2013/11/16 by Nate Derbinsky, Derbinsky, Nate, José Bento +3
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · #Artificial Intelligence (cs.AI) #DNA and Biological Computing #Digital Image Processing Techniques #FOS: Computer and information sciences #graph theory and CDMA systems

paper · pdf · doi:10.48550/arxiv.1311.4064

openalex publication_date 2013/11/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper we consider optimization as an approach for quickly and flexibly developing hybrid cognitive capabilities that are efficient, scalable, and can exploit knowledge to improve solution speed and quality. In this context, we focus on the Three-Weight Algorithm, which aims to solve general optimization problems. We propose novel methods by which to integrate knowledge with this algorithm to improve expressiveness, efficiency, and scaling, and demonstrate these techniques on two example problems (Sudoku and circle packing).

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