As with most, if not all, applications of reinforcement learning, there are always traditional algorithms that outperform it. But that does not mean that the approach lacks promise, or is at least interesting.
Sure, the paper might have polished up some results, but if that is the case, it is better addressed through the appropriate channels. Engaging in public criticism does not build too much trust, at least not with this curious observer.