University · Artificial Intelligence

Reinforcement Learning

Learning to act through reward-driven interaction with an environment

7 Lektionen

3 Karteikarten-Decks

3 Quizze

Lehrplan

Reinforcement Learning

MDPs, Value Iteration, and Policy Iteration1 Decks1 Quiz Q-Learning, SARSA, and Function Approximation1 Decks1 Quiz Deep RL: Policy Gradients and Actor-Critic Methods1 Decks1 Quiz

Reinforcement Learning

Multi-Agent Reinforcement Learning and Game Theory Model-Based Reinforcement Learning: World Models and Planning Exploration Strategies: Intrinsic Motivation, Curiosity, and UCB RL for Real-World Applications: Robotics, Games, and Combinatorial Optimisation

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