Better Earth-moving Machine Control through Artificial Intelligence

Benjamin shares how a program can learn to operate an earth-moving machine by itself using reinforcement learning and so operations that are difficult to simulate can be solved with little to no human input.

Benjamin Hodel, Analytics Tech Specialist at Caterpillar

Benj enjoys creating software solutions at the place where physical systems intersect applied science and analytics. Having received a BS in Mechanical Engineering from the University of Illinois Urbana-Champaign, Benj has worked at Caterpillar for over 16 years. He spent his early career as a developer of engineering data analysis software specializing in signal processing and is now an analytics technical specialist. He is currently leading the use of machine learning and deep learning technologies to make better Caterpillar products and solutions. He lives in Dunlap, Illinois, with his wife and three girls.

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