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Dr. Barrett Thomas, an award-winning Research Professor at the University of Iowa, explores the intricacies of Markov decision processes and their connection to Deep Reinforcement Learning. Discover how these concepts are applied in operations research to enhance business efficiency and drive innovations in same-day delivery and autonomous transportation systems.This episode is brought to you by Ready Tensor, where innovation meets reproducibility. Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information.In this episode you will learn:\u2022 Barrett's start in operations logistics [02:27]\u2022 Concorde Solver and the traveling salesperson problem [09:59]\u2022 Cross-function approximation explained [19:13]\u2022 How Markov decision processes relate to deep reinforcement learning [26:08]\u2022 Understanding policy in decision-making contexts [33:40]\u2022 Revolutionizing supply chains and transportation with aerial drones [46:47]\u2022 Barrett\u2019s career evolution: past changes and future prospects [52:19]Additional materials: www.superdatascience.com/773