A simple gridworld environment is implemented to demonstrate the Q-learning algorithm. The agent learns to navigate the grid and reach a goal state while avoiding obstacles. To try it out go to albheim.github.io/gridworld_qlearning_demo.
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A simple demo showing how q-functions update using a gridworld environment as example.
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albheim/gridworld_qlearning_demo
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A simple demo showing how q-functions update using a gridworld environment as example.
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