Effective Generation of Subjectively Random Binary Sequences

TL;DR

This paper introduces an algorithm designed to generate binary sequences that appear subjectively random to human observers, mimicking the unpredictability of genuine random processes.

Contribution

The paper proposes a novel algorithm that produces binary sequences perceived as highly random by humans, addressing the challenge of subjective randomness perception.

Findings

Sequences generated are rated as highly random by human evaluators

The algorithm outperforms previous methods in subjective randomness perception

Generated sequences closely resemble true random sequences in human assessments

Abstract

We present an algorithm for effectively generating binary sequences which would be rated by people as highly likely to have been generated by a random process, such as flipping a fair coin.