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Related lectures (31)

Learning with Simulations: Orchestration Graphs

Explores challenges in learning with simulations and introduces Orchestration Graphs.

Introduction to Reinforcement Learning: Concepts and Applications

Introduces reinforcement learning, covering its concepts, applications, and key algorithms.

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Explores the gap between AI and human intelligence through neuroscience-inspired models and algorithms.

Turbulent Flows Simulation

Discusses simulating turbulent flows and addresses student feedback and project challenges.

Interactive Lecture: Reinforcement Learning

Explores advanced reinforcement learning topics, including policies, value functions, Bellman recursion, and on-policy TD control.

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Explores the impact of spatial configuration on teaching interactions in classrooms, analyzing seating arrangements and teacher movements.

Landscape and Generalisation in Deep Learning

Explores the challenges and insights of deep learning, focusing on loss landscape, generalization, and feature learning.

Learning and Adaptive Control for Robots: Extensions to DS

Explores coupled and uncoupled dynamical systems, stability, hand-arm coupling, and adaptation in robotics.

Game Theory Applications: Project Proposals and Examples

Provides guidance on project proposals in game theory, showcasing past examples and emphasizing problem formulation and mathematical modeling.

Learning and Adaptive Control for Robots

Explores learning, adaptive control, cutting soft tissue, and robotic implementation for robots.

Collective Learning Dynamics: Similarity Exploitation

Delves into collective learning dynamics with similarity exploitation, covering structured learning, adaptive frameworks, modeling, simulation, and experimental results.

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