From Rules to Rewards: The Role of Domain Knowledge in Rules Based AI and Reinforcement Learning
How do cars learn to drive? How do computers defeat world champions in games like Go and Poker? As actuaries, we most often interact with the supervised learning paradigm of machine learning and spend less time thinking about rules-based AI and reinforcement learning. Rules-based AI encodes domain expertise into intelligent systems, whereas reinforcement learning enables agents to discover optimal behaviors by interacting with their environment. This session of Akur8 Academy with Actuarial Data Scientists Josh Myers and Max Martinelli will dive into both approaches, highlights what is and isn't relevant for actuaries, and challenges us to utilize these methods to be more proactive and improve our decision making.
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From Rules to Rewards: The Role of Domain Knowledge in Rules Based AI and Reinforcement Learning
How do cars learn to drive? How do computers defeat world champions in games like Go and Poker? As actuaries, we most often interact with the supervised learning paradigm of machine learning and spend less time thinking about rules-based AI and reinforcement learning. Rules-based AI encodes domain expertise into intelligent systems, whereas reinforcement learning enables agents to discover optimal behaviors by interacting with their environment. This session of Akur8 Academy with Actuarial Data Scientists Josh Myers and Max Martinelli will dive into both approaches, highlights what is and isn't relevant for actuaries, and challenges us to utilize these methods to be more proactive and improve our decision making.
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Learn more about the speakers
Josh Meyers
Josh Meyers is an Actuarial Data Scientist at Akur8. In his role, Josh works with clients helping them use models to solve business problems and gain insights with Akur8's software. Prior to joining Akur8, Josh spent five years at The Hartford where he held various pricing and modeling roles. He graduated from Brigham Young University with Master of Science in Statistics, and is currently a Fellow of the Casualty Actuarial Society (CAS).
Max Martinelli
Max Martinelli is a Lead Actuarial Data Scientist at Akur8, where he spearheads machine learning initiatives for P&C pricing for the North American market. With a background in predictive modeling, actuarial analytics, and computational mathematics, Max brings both technical depth and practical expertise to his clients. A dedicated collaborator with the Casualty Actuarial Society, he has played a key role in advancing AI initiatives—co-authoring and leading the CAS AI Fast Track Bootcamp and co-hosting Almost Nowhere, the CAS Institute’s new podcast exploring AI and Data Science in insurance.
