Solving multiplayer games with function approximation
The post Playing Connect Four with Deep Q-Learning appeared first on Towards Data Science.
Playing Connect Four with Deep Q-Learning
Towards Data Science / 5/4/2026
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Key Points
- The article describes using Deep Q-Learning to solve the multiplayer game Connect Four using function approximation rather than tabular methods.
- It frames the problem as learning an action-value policy by training a neural network to estimate Q-values from game states.
- The piece emphasizes applying reinforcement learning techniques to game environments where the state and action spaces can be large or complex.
- It presents the overall approach as an educational example of how deep RL can be used to learn effective gameplay strategies.
