Inspired by genetic programming (GP), we study iterative algorithms for non-computable tasks and compare them to naive models. This framework justifies many practical standard tri...
Abstract. We investigate systematically into the various possible notions of traceable sets and the relations they bear to each other and to other notions such as diagonally noncom...
Developing agents for simulation environments is usually the responsibility of computer experts. However, as domain experts have superior knowledge of the intended agent behavior, ...
As we devise more complicated prior distributions, will inference algorithms keep up? We highlight a negative result in computable probability theory by Ackerman, Freer, and Roy (...
We study the empirical meaning of randomness with respect to a family of probability distributions P, where is a real parameter, using algorithmic randomness theory. In the case w...