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Explore the fascinating world of soaring flight and airborne wind energy through this insightful 33-minute conference talk by Antonio Celani. Delve into the complexities of aerodynamics in turbulent atmospheres and discover how reinforcement learning can be applied to develop near-optimal control strategies for both bird-like soaring and kite-based power extraction. Gain a comprehensive understanding of the subject through topics such as naturalistic observations, virtual bird simulations, kite cycles, and prototypes. Examine numerical simulations, dynamical system analysis, and future prospects in multi-agent navigation. Engage with schematic representations and participate in a thought-provoking discussion on this cutting-edge intersection of biology, physics, and artificial intelligence.
Learning to Fly High: Reinforcement Learning for Soaring and Airborne Wind Energy