On the generation of high-quality random numbers by two-dimensional cellular automata
Abstract
Finding good random number generators (RNGs) is a hard problem that is of crucial import in several fields, ranging from large-scale statistical physics simulations to hardware self-test. In this paper, we employ the cellular programming evolutionary algorithm to automatically generate two-dimensional cellular automata (CA) RNGs. Applying an extensive suite of randomness tests to the evolved CAs, we demonstrate that they rapidly produce high-quality random-number sequences. Moreover, based on observations of the evolved CAs, we are able to handcraft even better RNGs, which not only outperform previously demonstrated high-quality RNGs, but can be potentially tailored to satisfy given hardware constraints.
- Publication:
-
IEEE Transactions on Computers
- Pub Date:
- October 2000
- DOI:
- Bibcode:
- 2000ITCmp..49.1146T
- Keywords:
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- Random number generation;
- Hardware;
- Content addressable storage;
- Large-scale systems;
- Physics;
- Built-in self-test;
- Automatic programming;
- Genetic programming;
- Evolutionary computation;
- Testing