Reinforcement Learning
Master of Science in Computer Science · University · Artificial Intelligence
This unit introduces the fundamental concepts of reinforcement learning, including Markov decision processes, Q-learning, and deep reinforcement learning. Students will gain a comprehensive understanding of how reinforcement learning algorithms work and how to apply them to real-world problems.
Zum Üben gibt es 51 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Introduction to reinforcement learning
- Markov decision processes
- Value functions
- Policy evaluation
- Policy improvement
- Q-learning
- Deep reinforcement learning
- Exploration vs exploitation
- Temporal difference learning
- Actor-critic methods
Stichworte
- Reinforcement Learning
- Markov Decision Processes
- Deep Reinforcement Learning
- Value Functions
- Policy Evaluation
- Policy Improvement
- Exploration vs Exploitation
- Temporal Difference Learning
- Actor-Critic Methods