An approach to integration of the analytical and empirical learning strategies for solving the theory-based concept specialization problem is proposed. The emphasis is on learning correct concepts within conjunctive description language isolated from supplied domain theory. In order to overcome expressive limitations of such language, the analytical learning component is guided by a speci ̄c emp...

background universities, like any other organization, are working in a variable and dynamic environment. in order to empower these organizations to deal with constant change, they should focus on organizational learning. objectives this research aimed to study the relationship between organizational learning and employees' empowerment among the headquarters staff of shiraz university of medical...

although organizational learning is often known as a goal, in the view of many stakeholders, the final aim of many organizations is optimization of financial results such as productivity, and  innovation is among various factors which optimizes the organizations financial performance, however, as firms seek financial performance improvement, higher profit and minimum cost, it is necessary to un...

Molecular-orbital-based machine learning (MOB-ML) enables the prediction of accurate correlation energies at cost obtaining molecular orbitals. Here, we present derivation, implementation, and numerical demonstration MOB-ML analytical nuclear gradients, which are formulated in a general Lagrangian framework to enforce orthogonality, localization, Brillouin constraints on The gradient is with re...

We describe a new approach for learning procedural knowledge represented as Teleoreactive Logic Programs (TLPs) using relational behavior traces as input. A TLP organizes task decomposition skills hierarchically and attaches them explicitly defined goals. Our approach integrates analytical learning with inductive generalization in order to learn these skills. The analytical component predicts t...