Efficient Necessary-and-Sufficient Conditions for Pareto-Point Achievability

Characterize efficiently checkable necessary and sufficient conditions under which Pareto-optimal points for probabilistic programs with nondeterminism are precisely achievable by determinizations rather than merely almost achievable.

Background

The framework characterizes almost-achievable trade-offs, meaning points that can be approached arbitrarily closely by mixed determinizations, and provides exact synthesis only under sufficient conditions such as suitable Scott-closedness and the existence of optimal determinizations for scalarized objectives.

The paper identifies the gap between almost achievability and exact achievability as a central limitation of its synthesis approach. The unresolved problem is to obtain conditions that are both necessary and sufficient and can be checked efficiently, thereby deciding when Pareto-optimal points are realized exactly.

References

Characterizing efficiently checkable necessary and sufficient conditions under which Pareto optimal points are (not just almost, but precisely) achievable remains an open problem.

Multiobjective Preexpectation Reasoning for Probabilistic Programs  (2608.13268 - Verscht et al., 13 Aug 2026) in Section 10, “Conclusion,” paragraph “Limitations”