/**
 * COST-AWARE — optimize per BAHT, not per experiment. Every other optimizer minimises the NUMBER of
 * experiments. But experiments don't cost the same: a high-temperature run burns more energy, a long assay
 * ties up the lab longer, a big-batch GPU sweep costs more compute. If you have a fixed BUDGET (money,
 * energy, machine-hours), the right goal is the best result per unit cost — and that can mean deliberately
 * avoiding an expensive region even when it looks slightly better.
 *
 * COST-AWARE proposes the next experiment by bang-per-buck: it weighs each candidate's optimistic potential
 * gain (a Lipschitz upper bound from your data) AGAINST its cost, and picks the best gain-per-cost. Within a
 * cost budget it reaches a strong result for far less spend than a cost-blind optimizer that wanders into
 * expensive corners.
 *
 * Honest by construction (DIAKRISIS): you supply the cost function; the gain is an optimistic estimate (it
 * over-weights unexplored regions, which is what you want for exploration); the win is measured, not claimed
 * — the gauntlet runs cost-aware vs cost-blind on the SAME cost budget and shows cost-aware reaches a higher
 * best. It is not guaranteed to find the global optimum if that optimum only lives in an unaffordably
 * expensive region — by design it won't bankrupt you chasing it.
 */
import { type Space, type Experiment } from "./space.js";
import { type Observation, type Goal } from "./engine.js";
type CostFn = (e: Experiment) => number;
/** Propose the next experiment by best optimistic-gain ÷ cost (bang-per-buck). */
export declare function proposeNextCostAware(space: Space, obs: ReadonlyArray<Observation>, goal: Goal, costFn: CostFn, seed?: number): Experiment;
export interface CostAwareResult {
    best: Observation;
    totalCost: number;
    evaluations: number;
    goal: Goal;
}
/** Run a cost-budgeted discovery: keep proposing the best bang-per-buck experiment until the cost budget runs out. */
export declare function costAwareDiscover(opts: {
    space: Space;
    oracle: (e: Experiment) => number;
    costFn: CostFn;
    costBudget: number;
    goal?: Goal;
    seed?: number;
    maxEvals?: number;
}): CostAwareResult;
export declare function costAwareGauntlet(): {
    score: 0 | 100;
    checks: Array<{
        name: string;
        pass: boolean;
        detail: string;
    }>;
};
export {};
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