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Simulation study demonstrates that predictive information diverges from finite recoverability, indicating distinct roles for representation retention and estimator specificity.
This preprint tests whether predictive information in recent history survives compression and finite estimation in a truth-known discrete simulator. Compact representations retained exact information for some targets but not others. Independent Laplace tables failed to recover one target despite closed support. A nested estimator improved prediction but also produced a history gain in a Markov control. The results show that predictive information, representation retention, finite recoverability, and estimator specificity are distinct. This study is methodological, not a biological validation.
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Robin Langell (2026) studied this question.
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