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773: Deep Reinforcement Learning for Maximizing Profits, with Prof. Barrett Thomas
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Manage episode 411539826 series 2532807
Contenido proporcionado por Super Data Science: ML & AI Podcast with Jon Krohn and Jon Krohn. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Super Data Science: ML & AI Podcast with Jon Krohn and Jon Krohn o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
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 (https://www.readytensor.ai/). Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information. In this episode you will learn: • Barrett's start in operations logistics [02:27] • Concorde Solver and the traveling salesperson problem [09:59] • Cross-function approximation explained [19:13] • How Markov decision processes relate to deep reinforcement learning [26:08] • Understanding policy in decision-making contexts [33:40] • Revolutionizing supply chains and transportation with aerial drones [46:47] • Barrett’s career evolution: past changes and future prospects [52:19] Additional materials: www.superdatascience.com/773
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783 episodios
MP3•Episodio en casa
Manage episode 411539826 series 2532807
Contenido proporcionado por Super Data Science: ML & AI Podcast with Jon Krohn and Jon Krohn. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Super Data Science: ML & AI Podcast with Jon Krohn and Jon Krohn o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
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 (https://www.readytensor.ai/). Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information. In this episode you will learn: • Barrett's start in operations logistics [02:27] • Concorde Solver and the traveling salesperson problem [09:59] • Cross-function approximation explained [19:13] • How Markov decision processes relate to deep reinforcement learning [26:08] • Understanding policy in decision-making contexts [33:40] • Revolutionizing supply chains and transportation with aerial drones [46:47] • Barrett’s career evolution: past changes and future prospects [52:19] Additional materials: www.superdatascience.com/773
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