TY - JOUR AU - Speaker, Paul AU - MacCluer, C. R. PY - 2011/12/01 Y2 - 2024/03/29 TI - Using Random Sets to Model Learning in Manufacturing JF - Journal of Informatics and Mathematical Sciences JA - Jour. Inform. Math. Sci. VL - 3 IS - 3 SE - Research Articles DO - 10.26713/jims.v3i3.51 UR - http://rgnpublications.com/journals/index.php/jims/article/view/51 SP - 201-210 AB - It is widely observed that  manufacturing quality metrics improve as experience is gained during production. The traditional empirical <em>learning curves</em> modeling such improvements have recently been explained by a predictive model deduced from first principles, namely certain principles imported into artificial intelligence from statistical mechanics. However, this new learning model  is limited to a finite lesson pool of paradigm shifts. This paper presents an extension to incremental learning using  sampling based on  the notion of dynamic random sets. ER -