Papers

Cross-entropy optimization with prioritized constraints

This preprint introduces TierCEM, a variant of the cross-entropy method that enforces an ordered sequence of constraints during elite selection, removing the need for per-constraint penalty weights. In exact and learned world-model Push-T tests, reversing the priority order switched which constraint was violated, and putting task progress first let lower-priority constraints relax so progress continued. For robot planners facing conflicting safety and task requirements, this offers a more explicit and tunable-free way to specify which rules yield first.