/**
 * Seedable PRNG for reproducible training.
 *
 * The package previously used `Math.random()` everywhere — fast but
 * non-deterministic, which breaks reproducible training, A/B mode comparison,
 * and unit tests that assert on stochastic behavior.
 *
 * This module exposes a Mulberry32-based PRNG (small, fast, statistically
 * sound for non-cryptographic use) plus a global injection point. RL
 * algorithms, weight initialization, and exploration policies should call
 * `random()` / `randomInt()` / `randomNormal()` from here instead of
 * `Math.random()` directly.
 *
 * For deterministic runs:
 *
 *   import { setGlobalRng, Mulberry32 } from '@claude-flow/neural';
 *   setGlobalRng(new Mulberry32(42));
 *
 * After that, all `random()` consumers produce the same sequence on
 * every run. Pass a different seed to vary the trajectory.
 */
export interface RNG {
    /** Uniform sample in [0, 1) */
    next(): number;
    /** Integer sample in [min, max) */
    nextInt(min: number, max: number): number;
    /** Standard normal sample (Box-Muller) */
    nextNormal(): number;
    /** Reseed in place (mutates this instance) */
    seed(s: number): void;
}
/**
 * Mulberry32 — 32-bit chaotic-state PRNG. Period 2^32, passes BigCrush
 * subtests, ~5x faster than seedrandom. Not cryptographically secure.
 */
export declare class Mulberry32 implements RNG {
    private state;
    constructor(seedValue?: number);
    next(): number;
    nextInt(min: number, max: number): number;
    nextNormal(): number;
    seed(s: number): void;
}
/**
 * Math.random()-backed RNG for backward compatibility / production default.
 * Fast, non-deterministic, what the package shipped with before.
 */
export declare class MathRandomRng implements RNG {
    next(): number;
    nextInt(min: number, max: number): number;
    nextNormal(): number;
    seed(_s: number): void;
}
/**
 * Replace the global RNG. Pass a `Mulberry32(seed)` for reproducible runs,
 * or any custom RNG impl for testing. Idempotent.
 */
export declare function setGlobalRng(rng: RNG): void;
/** Get the current global RNG (mainly for tests/diagnostics). */
export declare function getGlobalRng(): RNG;
/** Reset to the default `Math.random()`-backed RNG. Mainly for tests. */
export declare function resetGlobalRng(): void;
/** Convenience: uniform sample in [0, 1) using the global RNG. */
export declare function random(): number;
/** Convenience: integer sample in [min, max) using the global RNG. */
export declare function randomInt(min: number, max: number): number;
/** Convenience: standard normal sample using the global RNG. */
export declare function randomNormal(): number;
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