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

 

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.

November 15, 2013
AAAI Fall Symposium on Integrated Cognition 2013

 

Authors

Nate Derbinsky (Disney Research)

Jose Bento (Disney Research)

Jonathan Yedidia (Disney Research)

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

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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