Nan Jiang

Nan Jiang takes us deep into Model-based vs Model-free RL, Sim vs Real, Evaluation & Overfitting, RL Theory vs Practice and much more!

Nan Jiang is an Assistant Professor of Computer Science at University of Illinois.  He was a Postdoc Microsoft Research, and did his PhD at University of Michigan under Professor Satinder Singh. 

Featured References 
Additional References 

  • [Robin] I misspoke when I said in domain randomization we want the agent to "ignore" domain parameters.  What I should have said is, we want the agent to perform well within some range of domain parameters, it should be robust with respect to domain parameters. 

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