It's incredibly sad that control theorists spent so much time working out analytic solutions to dynamical systems, only to be so thoroughly beaten by Reinforcement Learning.
The recent successes of Alpha Go, Alpha Go Zero, as well work at OpenAI and Berkeley (especially on the incredibly physically-accurate simulator MuJuCo) show that the era of classical controls is dead. Indeed, it may be the case that seeking analytic solutions to problems like this is an artifact of a time when computation was expensive and human time was cheap.
In fact, recent work on robots learning to play with themselves from OpenAI [https://blog.openai.com/competitive-self-play/] suggests that in the near future, humans won't be needed for designing these algorithms at all!
The recent successes of Alpha Go, Alpha Go Zero, as well work at OpenAI and Berkeley (especially on the incredibly physically-accurate simulator MuJuCo) show that the era of classical controls is dead. Indeed, it may be the case that seeking analytic solutions to problems like this is an artifact of a time when computation was expensive and human time was cheap.
In fact, recent work on robots learning to play with themselves from OpenAI [https://blog.openai.com/competitive-self-play/] suggests that in the near future, humans won't be needed for designing these algorithms at all!