Abstract
Recently, Schmidhuber proposed a new concept of generalized algorithmic complexity. It allows for the description of both finite and infinite sequences. The resulting distributions are true probabilities rather than semimeasures. We clarify some points for this setting, concentrating on Enumerable Output Machines. As our main result, we prove a strong coding theorem (without logarithmic correction terms), which was left as an open problem. To this purpose, we introduce a more natural definition of generalized complexity.
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