- Implemented scripts/train_ai.py for institutional XGBoost training on MT5 historical candles
- Integrated 46 multi-indicator features, TimeSeriesSplit validation, and feature importance drivers
- Added --train-only and improved --train in main.py
- Enabled MT5 AutoTrading configuration ([Experts] AllowLiveTrading=1)
- Added send_pending_order and cancel_order to MT5Connector (BUY_LIMIT, SELL_LIMIT, BUY_STOP, SELL_STOP)
- Added automatic 12-hour periodic model retraining job in BotScheduler and TradingBot
- Updated Telegram Command Center with MT5 standalone fallback and pending order telemetry
- Placed live test BUY market trade and scheduled BUY_LIMIT order on XAUUSD
- Implemented TradeLearner with post-mortem mistake diagnostics and defensive rule formulation
- Added Mistake Memory Guard to screen prospective signals against past loss patterns and traps
- Dynamic Multi-Armed Bandit strategy multipliers (Scalping, Day, Swing) and adaptive confluence weighting
- Integrated with TradeExecutor, Bot position synchronization, and SignalAggregator
- Real-time Self-Learning HUD in modern glassmorphic web dashboard (/api/learning)
- Added /learning command and interactive callback button to Telegram Command Center
- Added TradeLesson and AdaptiveWeight persistence models in SQLite WAL database
- Updated documentation and README