claude-flow
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Ruflo - Enterprise AI agent orchestration for Claude Code. Deploy 60+ specialized agents in coordinated swarms with self-learning, fault-tolerant consensus, vector memory, and MCP integration
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TypeScript
/**
* Deep Q-Network (DQN)
*
* Implements DQN with enhancements:
* - Experience replay
* - Target network
* - Double DQN (optional)
* - Dueling architecture (optional)
* - Epsilon-greedy exploration
*
* Performance Target: <10ms per update step
*/
import type { DQNConfig, Trajectory } from '../types.js';
/**
* Default DQN configuration
*/
export declare const DEFAULT_DQN_CONFIG: DQNConfig;
/**
* DQN Algorithm Implementation
*/
export declare class DQNAlgorithm {
private config;
private qWeights;
private targetWeights;
private qMomentum;
private buffer;
private bufferIdx;
private epsilon;
private stepCount;
private numActions;
private inputDim;
private updateCount;
private avgLoss;
constructor(config?: Partial<DQNConfig>);
/**
* Add experience from trajectory
*/
addExperience(trajectory: Trajectory): void;
/**
* Perform DQN update
* Target: <10ms
*/
update(): {
loss: number;
epsilon: number;
};
/**
* Get action using epsilon-greedy
*/
getAction(state: Float32Array, explore?: boolean): number;
/**
* Get Q-values for a state
*/
getQValues(state: Float32Array): Float32Array;
/**
* Get statistics
*/
getStats(): Record<string, number>;
private initializeNetwork;
private copyNetwork;
private forward;
private accumulateGradients;
private applyGradients;
private sampleBatch;
private hashAction;
private argmax;
}
/**
* Factory function
*/
export declare function createDQN(config?: Partial<DQNConfig>): DQNAlgorithm;
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