/**
 * 🛡 AEGIS — the Self-Aware Engine. Every optimizer on earth chases the single highest number. AEGIS refuses
 * to. A tall spike perched on a cliff edge is a trap: it scores beautifully in the lab and fails the morning
 * the temperature drifts 1°, the reagent batch changes, the operator's hand wobbles. AEGIS optimizes for the
 * value that SURVIVES the real world — it watches its own search, learns where the cliffs and fragile spikes
 * are, and deliberately steers toward a broad, stable optimum, even when a more fragile setting scores
 * slightly higher.
 *
 * This is what makes it "self-aware": the same diagnostics Melete reports to humans (local steepness, cliff
 * proximity, robustness) are fed back IN to drive the engine. Its acquisition isn't "highest predicted
 * value" — it's "highest predicted value that also holds when you nudge it." And its final answer isn't the
 * raw maximum, it's the best ROBUST optimum. No competitor's optimizer does this: they hand you the spike,
 * then act surprised when it doesn't reproduce.
 *
 * Honest by construction (DIAKRISIS): robustness is estimated from your real data — how much the value
 * changes for a small move, measured from the nearest measurements — not assumed. AEGIS trades a little raw
 * peak height for a lot of stability; if you genuinely want the absolute spike, a plain maximiser still
 * exists. The gauntlet proves it head-to-head: on a tall-fragile-spike-vs-broad-stable-peak landscape, AEGIS
 * returns the setting that survives a real-world wobble while a plain maximiser returns the one that collapses.
 */
import { type Space, type Experiment } from "./space.js";
import { type Observation, type Goal } from "./engine.js";
export interface AegisResult {
    best: Observation;
    rawBest: Observation;
    robustnessOfBest: number;
    tradedHeight: number;
    evaluations: number;
    obs: Observation[];
}
/**
 * Run a self-aware discovery: search with a robustness-weighted acquisition and return the best STABLE
 * optimum (not the fragile spike). `robustWeight` 0 = pure height (a normal maximiser), 1 = strongly favour
 * flat regions.
 */
export declare function aegisDiscover(opts: {
    space: Space;
    oracle: (e: Experiment) => number;
    budget: number;
    goal?: Goal;
    seed?: number;
    robustWeight?: number;
}): AegisResult;
export declare function aegisGauntlet(): {
    score: 0 | 100;
    checks: Array<{
        name: string;
        pass: boolean;
        detail: string;
    }>;
};
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