In this episode of The Flux, John Cordier interviews Rob Axtell fromGeorge Mason University, where he leads the largest graduate programin agent-based modeling (ABM) globally. Axtell shares his journey intocomplex systems modeling and how the field has evolved since the1990s. He explains how George Mason’s Ph.D. program inComputational Social Science is shaping the next generation of expertswho go on to roles in government, research, and the private sector.They discuss the power of agent-based models to simulate real-worlddynamics, from consumer behavior to macroeconomics, highlighting theincreasing availability of data and computing power that allows ABM tocompete with traditional models used by institutions like central banks.Axtell emphasizes the need for more empirical grounding in ABM andthe potential to build large-scale, highly detailed models, including theexciting possibility of simulating entire economies.Axtell also touches on the importance of modeling social complexity atthe individual level, the challenges of past limitations in data, and theunique potential of ABM to provide a more accurate picture of systemslike financial markets.For those new to the field, Axtell offers practical advice on gettingstarted, emphasizing the value of tools like NetLogo as a gateway toABM. Whether you're a student, researcher, or data enthusiast, thisepisode provides a deep dive into the cutting-edge applications of ABMand its future impact.00:00 Welcome to The Flux Podcast00:18 Meet Rob Axtell: Expert in Agent-Based Simulation01:07 Overview of George Mason's Computational Social Science Program01:45 Career Paths for Graduates03:34 Rob Axtell Journey into Agent-Based Modeling05:58 The Evolution and Impact of Agent-Based Models08:37 Applications and Future of Agent-Based Modeling11:35 Challenges and Opportunities in Agent-Based Modeling14:06 The Importance of High-Fidelity Models16:31 Policy Implications and Real-World Applications29:41 Technical Advances and Future Directions36:44 Advice for Aspiring Agent-Based Modelers39:09 Conclusion and Final Thoughts

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