![]() Bearing this definition of a run in mind, it has been shown that humans tend to produce systematically biased series, switching too often between entries, and thus underrepresenting long runs in their generated series 8, 11. To better understand sequential independence in human RSG, let us first define a run in a series as a sequence of the same entry. However, regardless of the number of items, they fail to make those series sequentially independent 1, 8 (see Tune 9 and Wagenaar 10 for reviews of the classic literature on this topic). It has thus been shown that, when instructed to carry out RSG, humans can generate series that are empirically equiprobable when the number of items to randomize is small-e.g., 0’s and 1’s or rock, paper, scissors-though less so for a larger number of items-e.g., the digits from 0 to 9 7. However, research has also been carried out specifically on the behavioral, cognitive, and neural underpinnings of RSG in humans. Randomness-particularly Random Series Generation (RSG)-is often used in neuroscience and psychology to increase cognitive load-e.g., as a distractor task from a main task 4, 5, 6. In other words, sequential independence means that any entry in a series is not influenced by the entries before it (or after it). Formally, for a binary series \(=b\right)\). ![]() Nevertheless, characteristics that have been associated with random series include equiprobability of terms and sequential independence 1. It has been debated whether true randomness exists in nature some have even further claimed that randomness cannot be clearly defined 1, 2. Furthermore, we found that the underrepresentation of long repetitions of the same entry in the series explains up to 29% of the variability in human RSG, and we discuss what might make up the variance left unexplained. In addition, the higher RSG in the game setting does not transfer outside the game environment. ![]() However, our results also suggest that human RSG cannot be further improved by explicitly informing participants that they need to be random to win. Using a compressibility metric of randomness, our results demonstrate that human RSG can reach levels statistically indistinguishable from computer pseudo-random generators in a competitive-game setting. During the game, we manipulated participants’ level of awareness of the computer’s strategy they were either (a) not informed of the computer’s algorithm or (b) explicitly informed that the computer used patterns in their choice history against them, so they must be maximally random to win. To investigate this, we designed a pre/post intervention paradigm around a Rock-Paper-Scissors game followed by a questionnaire. Nor is it known whether any such improvement in RSG transfers outside the game environment. ![]() However, it remains unclear how random people can be during games and whether RSG during games can improve when explicitly informing people that they must be as random as possible to win the game. The human ability for random-sequence generation (RSG) is limited but improves in a competitive game environment with feedback.
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