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Reinforcement learning coding challenges

Practise reinforcement learning with 3 coding challenges, from easy to hard. Every challenge runs in your browser with instant tests, an AI review of your code and community solutions to compare.

Easy · 1 Medium · 2

Skills you'll practise: BanditsBellman equationDiscounted rewardsExplore vs exploitMDPsQ-learning
  • Python · C++ · C#
  • Automated tests
  • AI code review
  • Community solutions
Programming
Programming fundamentalsFrom variables to recursion, for beginners
AI and machine learning
AI Learning HubNeural networks, ML and LLMs from scratch Neural networks from scratchNeurons, backpropagation and optimizers Machine learning from scratchRegression, classification and clustering Transformers and LLMs from scratchTokenizers, attention and text generation Classical AI and reinforcement learningSearch, games and reinforcement learning
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3 challenges
Medium

Value Iteration

Compute how valuable each state of a Markov decision process is by repeatedly applying the Bellman optimality update.

You'll learn Bellman equationMDPs
Reinforcement learningaimachine learning
Python C++ C#
0 solved
No solutions yet
Medium

Q-Learning Updates

Apply the Q-learning update to a stream of experiences and watch rewards flow back to earlier states.

You'll learn Q-learningDiscounted rewards
Reinforcement learningaimachine learning
Python C++ C#
0 solved
No solutions yet
Easy

Epsilon-Greedy Multi-Armed Bandit

Balance exploration and exploitation on a multi-armed bandit with epsilon-greedy action selection.

You'll learn Explore vs exploitBandits
Reinforcement learningaimachine learning
Python C++ C#
0 solved
No solutions yet

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