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.

翻译：我们讨论了在竞争环境中追求对抗目标的通用学习算法的概念局限性,并证明它们受到类似于G\“odel”和图灵著名理论对知识的限制的限制。 这些局限性与竞争性环境中通常存在的不透明性有关。