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When Dynamics Models Agree and Still Fail
Within-model noise and between-model disagreement describe different uncertainty. An exact counterexample shows how shared bias escapes the second.
Analytic mixture moments for hand-specified predictors and a shared-bias counterexample; no fitted ensemble, trajectory optimizer, or PETS benchmark.
The code uses Python 3 and the standard library. Saved output is from the checked CPU run.
x=0.0 mean=0.000 within=0.04000 between=0.00000 total_sd=0.200 x=0.5 mean=0.500 within=0.04000 between=0.00667 total_sd=0.216 x=2.0 mean=2.000 within=0.04000 between=0.10667 total_sd=0.383 Shared-bias counterexample: x=0.5 error=0.125 disagreement=0.000 x=2.0 error=2.000 disagreement=0.000 Mixture second-moment checks: passed
Sources
- Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models: https://arxiv.org/abs/1805.12114
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