Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models
Controllers based on sampling and latent world models assign a predicted terminal cost to each candidate action sequence, choose the minimum, execute its first action block, and replan. This rule can fail even when the terminal cost perfectly and accurately reflects the true task objective in the physical world. Residual prediction error can give an infeasible sequence an anomalously low cost, and a larger proposal pool gives such errors more chances to outrank feasible alternatives. We call this conditional failure proposal overgeneration. In Cube candidate execution audits, increasing the total proposal budget from 72 to 288 reduces the feasibility of selection by minimum latent cost fr...
| Authors | Liangyu Li, Qingwen Liu, Mingqing Liu et al. |
|---|---|
| Primary category | cs.RO |
| Published | 26 July 2026 |
| Last updated at source | 31 August 2026 |
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