This is a simple implementation Deep Q-learning algorithm in pytorch. the agent can move in four directions. going on green squares gives the model a reward while going on red squares punishes the model. the model should find a way to maximize number of rewards in 10 steps
this graph shows the changes in total rewards gained by the model after 30 runs.
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Simple Deep Q Reinforcement learning
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