I found the problem of governing a public resource by a single agent a novel one. This problem has many useful and hard to solve real word applications.

I also liked the approach taken to learn a voting scheme that cannot be manipulated by individual sources such that the output policy learned by the agent is optimal in terms of the preferences of any given source. By choosing votes that obey the Nash equilibrium, the algorithm ensures that it is in the best interest of any given source to train the agent according to the true preference of that source.

I felt like the both of the problems and its difficulties could have been explained more clearly. A simple explanation, like the one given by Eric, about what the examples show would have been also very helpful.