RL is slow?
Large state spaces are hard for RL?!
RL does not work well with function approximation?!
Non-Markovianness invalidates standard RL methods?!
POMDPs are hard for RL to deal with?!
In the opinion of Satinder Singh, these are myths of RL. He answers to these myths and expresses that these are not true beliefs. Moreover, there are many other information about reinforcement learning (myths, success, and …) in The University of Michigan Reinforcement Learning Group.