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Most of the literature on Reinforcement Learning discuss Hamilton Jacobi Bellman equations for optimality. In dynamics however Ricatti equations are used. I am curious if there are any parallels between the two equations for optimality? How do one differ from the other?

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  • $\begingroup$ Hi: ricatti results from kalman filter theory. hjb results from optimal control theory. not sure of the relation but, if there is one, it's not obvious. I would google for them together and see if anything pops up. $\endgroup$ – mark leeds Jun 30 at 16:23
  • $\begingroup$ @markleeds What I read is ricatti also results from optimal control. This is why I was trying to find a link between the two. Will keep looking, thanks. $\endgroup$ – GENIVI-LEARNER Jun 30 at 18:02
  • $\begingroup$ that's news to me but it definitely then indicates a serious connection. there should be a ton of material out there for sure. I'm sorry that I can't be of more help. $\endgroup$ – mark leeds Jun 30 at 19:22
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    $\begingroup$ Hi: I don't have time to read it but his talks about solving a differential riccati and then using that to solve hjb. ocw.mit.edu/courses/aeronautics-and-astronautics/… $\endgroup$ – mark leeds Jun 30 at 19:23
  • $\begingroup$ @markleeds thanks a lot. I will give it a read. $\endgroup$ – GENIVI-LEARNER Jul 1 at 12:11

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