Population Computation and Majority Inference in Test Tube

Abstract

We consider a probabilistic interpretation of the test tube which contains a large amount of DNA strands, and propose a population computation using a number of DNA strands in the test tube and a probabilistic logical inference based on the probabilistic interpretation. Second, in order for the DNA-based learning algorithm [4] to be robust for errors in the data, we implement the weighted majority algorithm [3] on DNA computers, called DNA-based majority algorithm via amplification (DNAMA), which take a strategy of “amplifying” the consistent (correct) DNA strands while the usual weighted majority algorithm decreases the weights of inconsistent ones. We show a theoretical analysis for the mistake bound of the DNA-based majority algorithm via amplification, and imply that the amplification to “double the volumes” of the correct DNA strands in the test tube works well.

This work is supported in part by “Research for the Future” Program No. JSPS-RFTF 96I00101 from the Japan Society for the Promotion of Science.