Beyond the Black Box: Interpretable Models of Human Randomisation Failures
Mixed strategy equilibrium predicts i.i.d play: past actions should not help predict future decisions. Human players, however, systematically depart from this benchmark, and in O'Neill's zero sum card game, these departures can be predicted by black box sequence models such as LSTMs. This paper asks whether that predictive power can be achieved by transparent alternatives that also reveal the behavioural structure behind it. Using 84,060 decisions from 2,802 pairs, the analysis first benchmarks naive and behavioral models against interpretable machine learning and deep learning models, then evaluates the modified EWA specifications of prior work against these benchmarks and uses the LASSO...
| Authors | Ngoc Linh Dao |
|---|---|
| Primary category | cs.AI |
| Published | 7 August 2026 |
| Last updated at source | 7 August 2026 |
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