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Abstract NetLogo, probably the most widely used agent-based modeling (ABM) platform, is designed to have a "low threshold and high ceiling," meaning that it is easy to get started but can also be used for advanced research. NetLogo has succeeded on both of these fronts, being widely used both in educational settings and by professional researchers. This session will provide a tour of some of NetLogo's advanced features which "raise the ceiling" of what it can do including: new BehaviorSpace features for running complex experiments, BehaviorSearch for finding parameter combinations in high dimensional search spaces that lead to target emergent patterns, discrete event scheduling as an alternative to tick-based scheduling, LevelsSpace for embedding ABMs inside of other ABMs, and the much-improved GIS extension. Speaker's Bio Jacob Kelter is a PhD candidate in computer science and learning sciences at Northwestern University where he is a member of the Center for Connected Learning and Computer Based modeling which develops and maintains NetLogo. His dissertation research consists of two parts: (1) prototyping Morfli, a "morphable" learning infrastructure, which is designed based on complex systems principles to foster ongoing educational improvement by creating feedback loops between students, educators, and researchers and sharing findings/tools across the educational system and (2) working with a materials science and engineering (MSE) professor to re-design the introductory MSE course around agent-based models and then studying the learning outcomes. He also has published ABM-based studies of quadratic voting and the effect of introducing land constraints to macroeconomic ABMs.