/**
 * SEARCH SPACE — the set of experiments the brain may propose.
 *
 * A space is a list of dimensions, each real (continuous) or int (discrete-integer), with bounds. An
 * "experiment" is one point in that space (a Record<dim, number>). The brain proposes experiments; the
 * oracle returns a result per experiment. Deterministic: candidate generation is seeded, so a discovery
 * run is reproducible (which is what makes the signed trace meaningful).
 */
export interface Dim {
    name: string;
    type: "real" | "int";
    min: number;
    max: number;
}
export interface Space {
    dims: Dim[];
}
export type Experiment = Record<string, number>;
/** Deterministic LCG — reproducible across runs (no Math.random). */
export declare function lcg(seed: number): () => number;
export declare function clampExperiment(space: Space, e: Experiment): Experiment;
/** A coarse grid of `perDim` points per dimension (bounded cartesian) — the cold-start design of experiments. */
export declare function gridCandidates(space: Space, perDim?: number, cap?: number): Experiment[];
/** `n` deterministic random candidates (seeded) — the dense candidate pool the acquisition maximises over. */
export declare function randomCandidates(space: Space, n: number, rnd: () => number): Experiment[];
/** `n` candidates sampled in a shrinking Gaussian ball around a center — the local refinement that zooms
 * into an optimum (global random candidates alone can't hit a tight target precisely). radius ∈ (0,1] is a
 * fraction of each dimension's span. */
export declare function localCandidates(space: Space, center: Experiment, n: number, radius: number, rnd: () => number): Experiment[];
export declare function dist2(space: Space, a: Experiment, b: Experiment): number;
export declare function spaceGauntlet(): {
    score: 0 | 100;
    checks: Array<{
        name: string;
        pass: boolean;
    }>;
};
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