Reinforcement Learning via Stochastic Control
Explore reinforcement learning in continuous time and space, examining stochastic control theory's role and recent developments in this emerging field.
Global Guarantees for Policy Gradient Methods
Explore global guarantees for policy gradient methods in reinforcement learning, examining theoretical foundations and practical implications.
A Quiescent Regime for Big Bang Formation
Explore stable big bang formation in general relativity, covering recent results and a new condition for big bang formation in Einstein-non-linear scalar field settings.
Learning to Fly High: Reinforcement Learning for Soaring and Airborne Wind Energy
Explore reinforcement learning for soaring and airborne wind energy, focusing on optimal control strategies in turbulent atmospheric conditions.
Temporal Difference Learning for Model Predictive Control - Research Presentation 3
Presentation on Temporal Difference Learning for Model Predictive Control, exploring innovative approaches in robotics and AI. Insights into recent papers and project developments by researcher Nicklas Hansen.
Decision Awareness in Reinforcement Learning
Explore decision awareness in reinforcement learning, focusing on control-oriented transition models and neural ODEs for nonlinear trajectory optimization. Discuss computational challenges and scaling solutions.
Koopman Operator Theory Based Machine Learning of Dynamical Systems
Explore Koopman Operator Theory for machine learning of dynamical systems, covering applications in fluid dynamics, power grids, network security, and more.
Adversarial Machine Learning: Beyond Manipulating Pixels and Words
Explore vulnerabilities in sequential machine learning and challenge assumptions about imperceptible attacks on image classification through human behavioral studies.
Quadratic Stability of the Brunn-Minkowski Inequality
Delve into advanced mathematical concepts exploring the quadratic stability of Brunn-Minkowski inequality, its geometric implications, and connections to related inequalities in convex geometry.
Games and Filters: A Road to Safe Intelligence
Explore game-theoretic approaches and safety principles in AI systems, from robotic control to human-AI interactions, focusing on developing reliable safety guarantees for autonomous systems.
General AI Safety - The Development of Beneficial Artificial Intelligence
Delve into Stuart Russell's expert analysis of artificial general intelligence (AGI), exploring its potential implications, risks, and the crucial need for developing provably beneficial AI systems.
Sosyal Sistemlerde Otomasyon:Performans Ölçümü | Yağmur Denizhan | TEDxBeşiktaş Atatürk Anatolian HS
Doğadaki kararlı tüm süreçlerin işleyişinde başrol oynayan negatif geri-besleme prensibinden yararlanan otomatik kontrol yaklaşımı, uygun komutlar vererek teknolojik sistemlerin hedeflenen davranışı gerçekleştirmesini sağlar. Çağımızın teknolojik başarılarına damgasını vuran bu işleyişin temel mantı