On limitations of learning algorithms in competitive environments
  We discuss conceptual limitations of generic learning algorithms pursuing
adversarial goals in competitive environments, and prove that they are subject
to limitations that are analogous to the constraints on knowledge imposed by
the famous theorems of G\"odel and Turing. These limitations are shown to be
related to intransitivity, which is commonly present in competitive
environments.
