Question on recurrent version of NEAT

[dbsxdbsx]

After reading the early and the latter paper of NEAT, I still am not clear on the feature of NEAT for POMDP problem.

For instance, the game double-pole need velocity as a core property to solve. Without it , it is a POMDP problem. As far as I know, if deep reinforcement learning(DRL) is taken to solve a POMDP, hiddent state must be taken as another input for network with RNN structure. And the hidden state is the output from former-step of the network. Butt... According to NEAT, it seems that only standard input like in standard MDP in needed for network with RNN structure (which is envolved by itself)---Is this a correct explanation?

If so, does it mean that NEAT can solve POMDP without building complex RNN structure, and without changing standard state input (on stand of standard MDP)?