Abstract
Artificial general intelligence aims to create agents capable of learning to solve arbitrary interesting problems. We define two versions of asymptotic optimality and prove that no agent can satisfy the strong version while in some cases, depending on discounting, there does exist a non-computable weak asymptotically optimal agent. © 2011 Springer-Verlag.
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APA
Lattimore, T., & Hutter, M. (2011). Asymptotically optimal agents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6925 LNAI, pp. 368–382). https://doi.org/10.1007/978-3-642-24412-4_29
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