Assessing Human Intuition of Randomness

Washington, DC · May 2019

Poster · Cross-Cutting Theme Poster - Artificial Intelligence and Psychological Science

Robert Becklen
Ramapo College of New Jersey
Stephanie Pignatelli
Ramapo College of New Jersey
Sanjay Chhetri
Ramapo College of New Jersey

Abstract

The OACC garnered worldwide attention (https://www.hectorzenil.net/media.html) by promising to optimally assess the randomness of human generated binary sequences. This claim appears to be true for information-poor short sequences only. We show that a multivariable Baysean approach to model building outperforms OACC for longer sequences.

Cognitive Processes

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Assessing Human Intuition of Randomness

Abstract

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