The spectacular success of modern control theory realized by reinforcement learning suggests that many real-world problems can be solved via a new paradigm of simulation or ‘gamification’. Averting climate change, making mass-mobility sustainable through smart city control and large-scale fleet management, building safe self-driving cars, or revolutionizing any real-world logistics problem: With this new paradigm, a simulator (or game) is built that encompasses all salient features of a problem to be solved. Then, a self-learning AI algorithm plays the game until it finds a solution. Hence an entire class of hitherto intractable intelligent control theory problems has become accessible if one can build an expressive enough simulator.

 

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