/**
 * THE BRAIN — the closed-loop active-experiment-design engine.
 *
 *   propose  → the most promising UNtried experiment (Bayesian-optimization-lite: a Gaussian-kernel
 *              surrogate predicts the outcome of any candidate; an UCB acquisition trades off exploiting
 *              the best-known region against exploring the uncertain one; exploration DECAYS over the
 *              budget so it explores early and exploits late)
 *   observe  → the oracle measures the proposed experiment
 *   update   → the observation joins the evidence; the surrogate sharpens
 *   converge → repeat until the budget is spent or the goal is reached
 *
 * It learns the shape of an unknown response surface from as FEW experiments as possible — because in the
 * real world each experiment costs reagents / robot-time / money. Deterministic (seeded), so a run is
 * reproducible and its signed trace is meaningful.
 *
 * ★HONEST: this is a lightweight, dependency-free surrogate (kernel-weighted mean + nearest-point
 * uncertainty), not a full Gaussian-process with learned hyperparameters. It reliably beats random/grid
 * on smooth-ish response surfaces (proven in bench.ts); pathological/high-dimensional/very noisy surfaces
 * need a heavier surrogate — a slot the architecture leaves open.
 */
import { type Space, type Experiment } from "./space.js";
export type Goal = "maximize" | "minimize";
export interface Observation {
    experiment: Experiment;
    value: number;
}
export interface Step {
    n: number;
    experiment: Experiment;
    value: number;
    acquisition: number;
    kappa: number;
    rationale: string;
}
export interface DiscoveryResult {
    best: Observation;
    history: Step[];
    evaluations: number;
    converged: boolean;
    goal: Goal;
}
export interface DiscoverOpts {
    space: Space;
    oracle: (e: Experiment) => number | Promise<number>;
    budget: number;
    goal?: Goal;
    seed?: number;
    target?: number;
    candidatePool?: number;
    kappa0?: number;
    bandwidth?: number;
    haltonOffset?: number;
    coldStart?: number;
    onStep?: (s: Step) => void | Promise<void>;
}
/** Run the closed discovery loop. Returns the best experiment found + the full reproducible history. */
export declare function discover(opts: DiscoverOpts): Promise<DiscoveryResult>;
export declare function engineGauntlet(): Promise<{
    score: 0 | 100;
    checks: Array<{
        name: string;
        pass: boolean;
        detail: string;
    }>;
}>;
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