SalahEddineGhamri

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Simple Q learning algorithm with epsilon-greedy action choice

in q-learning algorithm we maintain a table of stats-actions q-values
after attributing the rewards to the goal states
the table is update based on bellman learning formula
to propagate the q values on the state-action back to the start

learning is done through episodes
in the end the result path is calculated from the learned policy