/**
 * MULTI-OBJECTIVE — real problems rarely have ONE goal. A pharma formulation must be more POTENT *and* more
 * STABLE *and* cheaper; a fraud model must catch more fraud *and* decline fewer good customers. These trade
 * off — there is no single best, but a PARETO FRONT of best-possible compromises.
 *
 * MULTI-OBJECTIVE finds that front from hand-measured results: you score each experiment on N objectives,
 * and Melete (a) computes the exact non-dominated set and (b) proposes the next experiment to widen the
 * front, by scalarising the objectives with a deterministically-varying weight vector so successive
 * proposals probe different trade-offs. Deterministic ⇒ reproducible + signable like every Melete run.
 *
 * Honest by construction (DIAKRISIS): the Pareto front (dominance) is EXACT. The proposer uses weighted-sum
 * scalarisation with rotating weights — simple, robust, and it reliably spreads along the front; it is not
 * guaranteed to recover points on a deeply CONCAVE front (a known limitation of linear scalarisation, the
 * honest trade-off for a dependency-free deterministic engine). The front it reports is always exact.
 */
import { type Space, type Experiment } from "./space.js";
export interface MGoal {
    name?: string;
    goal: "maximize" | "minimize";
}
export interface MObservation {
    experiment: Experiment;
    values: number[];
}
/** Does `a` Pareto-dominate `b` across all objectives (≥ in every one, > in at least one, in goal direction)? */
export declare function dominates(a: number[], b: number[], goals: ReadonlyArray<MGoal>): boolean;
/** The exact non-dominated set — the achievable best trade-offs. */
export declare function paretoFront(obs: ReadonlyArray<MObservation>, goals: ReadonlyArray<MGoal>): MObservation[];
/**
 * Propose the next experiment to widen the Pareto front. Scalarises the N objectives with a weight vector
 * that rotates with the run, so successive calls probe different corners of the trade-off space.
 */
export declare function proposeNextMulti(space: Space, obs: ReadonlyArray<MObservation>, goals: ReadonlyArray<MGoal>, seed?: number): Experiment;
export declare function multiObjectiveGauntlet(): {
    score: 0 | 100;
    checks: Array<{
        name: string;
        pass: boolean;
        detail: string;
    }>;
};
//# sourceMappingURL=multiobjective.d.ts.map