Northwestern Engineering faculty and students participated in the annual forum for advances in theory, empirics, and ...

This paper argues that a hybrid methodological framework, integrating data-driven tools with theoretical constructions from nonequilibrium statistical mechanics and network science, is essential for ...

In this work, a synergistic combination of deep reinforcement learning and hierarchical game theory is proposed as a modeling framework for behavioral predictions of drivers in highway driving ...

This article explores the theoretical framework of language learning motivation and its implications for research and practice in the field.

A review examines the prevailing theory of cancer evolution. The authors highlight both practical and theoretical limitations of the clonal model of cancer evolution and propose areas for ...

The dynamic shifts in educational settings have led scholars to explore online social networks (OSNs) as emergent environment for learning communities. Recognized for their effectiveness in fostering ...

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries?

Howard Gardner’s Theory of Multiple Intelligences offers a valuable psychological framework for comprehending these differences to consequently craft educational experiences that resonate with each ...

This study delves into the behavioral complexities of autism spectrum disorder (ASD) by introducing the rigid-autonomous phase sequence (RAPS) formation concept.