Introduction to Reinforcement Learning (2015)
I used to be a bit more excited about RL.  I mean, it's still definitely something I have to learn, but one aspect of it _seems_ lacking to me and is messing with my motivation to learn it.  I'm sure someone will happily explain all the ways I am ignorant.<p>It seems like there is a lot of emphasis on "direct RL" or whatever where they don't even really think about the model much, but it's I guess often inside of the policy or something?<p>But it seems to me as someone who has just started learning about robotics, that I absolutely need to first verify that I have an accurate model of the environment which I can inspect.  It seems like a lot of RL approaches might not even be able to supply that.<p>I mean what I am stuck on as far as creating a robot (or virtual robot) is having a vision system that does all of the hard things I want.  I feel like if I can detect edges and surfaces and shapes in 3D, parts of objects and objects, with orientation etc., and in a way I can display and manipulate it, that level of understanding will give me a firm base to build the rest of learning and planning on.<p>I know all of that is very hard.  It seems like they must have tried that for awhile and then kind of gave up to head down the current direction of RL?  Or just decided it wasn't important.  I still think it's important.