1. The recurrent network algorithms are not local in space.
2. As with all gradient descent algorithms there is the problem of local minima. This paper does not offer any solutions to this problem.
3. More severe limitations of the algorithm are inherent problems of the concepts of `gradient descent through time' and adaptive critics. Neither gradient descent nor adaptive critics are practical when there are long time lags between actions and ultimate consequences. For this reason, first steps are made in  towards adaptive sub-goal generators and adaptive `causality detectors'.