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← CoursesData Science AppliedModule 4 · Causal Inference & A/B TestingMulti-armed bandits: epsilon-greedywrite64 / 100
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📝 **Question:** Implement `EpsilonGreedy` and simulate 10000 pulls on 3 arms with true rewards [0.1, 0.5, 0.2]. Use `random.seed(42)` and `epsilon=0.1`. Print the final pull counts per arm (the winner should dominate). 📋 Pick the right answer. 💡 **Hint:** Re-read the theory above if unsure.

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