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Simulation and Optimization Competitions
Reinforcement learning (RL) is an interesting case among the different branches of machine learning. On the one hand, it is quite demanding from a technical standpoint: various intuitions from supervised learning do not hold, and the associated mathematical apparatus is quite a bit more advanced; on the other hand, it is the easiest one to explain to an outsider or layperson. A simple analogy is teaching your pet (I am very intentionally trying to steer clear of the dogs versus cats debate) to perform tricks: you provide a treat for a trick well done, and refuse it otherwise.
Reinforcement learning was a latecomer to the competition party on Kaggle, but the situation has changed in the last few years ...
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