Intelligent modeling with physics-informed machine learning for petroleum engineering problems

Evaluating machine learning models for engineering problems

The use of machine learning (ML), and in particular, artiicial neural networks (ANN), in engineering applications has increased dramatically over the last years. However, by and large, the development of such applications or their report lack proper evaluation. Deecient evaluation practice was observed in the general neural networks community and again in engineering applications through a surv...

Modeling and Debugging Engineering Decision Procedures with Machine Learning

This paper reports on the use of machine learning systems for modeling existing engineering decision procedures. In this activity, various models of an existing decision procedure are constructed by using diierent machine learning systems as well as by changing their operational parameters and input. Individual models serve to focus on diierent aspects of the decision procedure and their combin...

Modeling Machine Learning and Data Mining Problems with FO(·)

This paper reports on the use of the FO(·) language and the IDP framework for modeling and solving some machine learning and data mining tasks. The core component of a model in the IDP framework is an FO(·) theory consisting of formulas in first order logic and definitions; the latter are basically logic programs where clause bodies can have arbitrary first order formulas. Hence, it is a small ...

Machine Learning for Intelligent Agents

Machine Learning for Intelligent Systems

Recent research in machine learning has focused on supervised induction for simple classification and reinforcement learning for simple reactive behaviors. In the process, the field has become disconnected from AI’s original goal of creating complete intelligent agents. In this paper, I review recent work on machine learning for planning, language, vision, and other topics that runs counter to ...