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Warrior_EA/README.md
AnimateDread 8157c42314 feat: Enhance README and documentation for Warrior_EA project 
- Updated README.md with project overview, key features, directory structure, getting started guide, and modernization roadmap.
- Added AI_NETWORK.md detailing the neural network and AI/ML infrastructure, including architecture, components, usage patterns, and next steps.
- Introduced DATABASE.md for the Database module, outlining key components, design highlights, usage patterns, and future enhancements.
- Created README.md files for Enumerations, Expert, Money, Signals, Structures, System, Trailing, Variables directories, detailing their purpose, key components, and integration notes.
- Documented the Signals subsystem, emphasizing modularity, extensibility, and AI/ML readiness.
- Added comprehensive descriptions for individual signal modules in Signals/ directory.
- Established clear integration notes and recommendations for future improvements across all modules.
2026-04-20 19:28:34 -04:00

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Warrior_EA Project Overview

Description

Warrior_EA is a modular, AI/ML-ready MetaTrader 5 Expert Advisor designed for robust, production-grade trading. It integrates traditional and AI-driven signals, advanced money management, trailing stops, and a database/statistics subsystem for adaptive optimization.

Key Features

  • AI/ML Integration: LSTM, PAI, and CONV neural network signals, with configurable feature pipelines and training options.
  • Traditional Signals: Modular support for classic indicators (MA, MACD, RSI, etc.) and price action patterns.
  • Money Management: Fixed lot, fixed risk, and intelligent/adaptive strategies.
  • Trailing Stops: ATR-based, MA-based, Parabolic SAR, and more.
  • Database/Statistics: Tracks trades, signals, and performance for optimization and research.
  • Configurable Inputs: All major features and strategies are user-configurable via Inputs.mqh.
  • Robust Initialization: Retry logic and error handling for all critical subsystems.
  • Production-Ready: Designed for institutional and advanced retail use, with a focus on maintainability and extensibility.

Directory Structure

  • AI/: Neural network and ML logic
  • Database/: Database and statistics management
  • Enumerations/: Enum and type definitions
  • Expert/: Main EA orchestration and custom logic
  • Money/: Money management strategies
  • Signals/: Signal generation (AI and traditional)
  • Structures/: Data structures for signals and trades
  • System/: Utility and infrastructure modules
  • Trailing/: Trailing stop strategies
  • Variables/: Global input parameters and runtime variables

Getting Started

  1. Configure your desired strategies and features in Variables/Inputs.mqh.
  2. Compile Warrior_EA.mq5 in MetaEditor.
  3. Attach to a chart and enable Algo Trading.
  4. Monitor logs and database/statistics for performance and optimization.

Modernization & AI/ML Roadmap

  • Migrate all hard-coded signals to a configurable, feature-driven pipeline.
  • Expand AI/ML subsystem with new models and training options.
  • Enhance database/statistics for deeper analytics and automated optimization.
  • Introduce unit and integration tests for all modules.

Documented April 2026. For subsystem details, see each directory's README.md and AI_NETWORK.md.