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Implement Core Iteration Tracking Mechanism for Adaptive Learning Process

Description

Task

Implement core iteration tracking mechanism, including current iteration count, progression tracking, and basic state management.

Acceptance Criteria

  • Iteration tracking class successfully tracks and manages iteration state
  • Iteration counter works as expected with proper incrementation
  • State management supports basic tracking and progression
  • Error handling prevents invalid iteration scenarios
  • Configuration parameters can be applied to iteration tracking

Summary of Work

This pull request introduces a foundational iteration tracking mechanism for the Adaptive Learning Process (ALP) loop. The implementation will provide robust tracking of iteration state, including current iteration count, progression monitoring, and basic state management to support the system's adaptive learning capabilities.

Changes Made

  • Create base iteration tracking class with core state management
  • Implement iteration counter and progression tracking
  • Add basic error handling for iteration management
  • Develop initial configuration support for iteration parameters
  • Prepare for extensibility and future enhancements

Tests

  • Verify iteration counter increments correctly
  • Test state management and tracking functionality
  • Validate error handling for edge cases
  • Ensure configuration parameters are correctly applied
  • Check iteration progression tracking mechanisms

Signatures

Staking Key

63GuD6KX1ZByaB7nsnCuGZe2HfY4HfcMnHqHhiDXeAdf: QN2iJF6F1f4dK6p266i6VQXoksydqTAG9xvXLdXsj261tNCfyotGh1LnTKbu5E5DcAznnFh6QMqVa7HxSQfCvEzVjmXSbK1ZwerJLW34uvqDDqiw3ZXLniw4Jk3ZZLMohqqt2Q48eoxsaaowys9n17DjfciFnBMUhCHLffYCeSBxk73PLPijSDDCxgmM9cZ83trQaWTmZ4AiYnLG2sCJ1NT8cCxn85fYiJWoRwiZTBitQkUJ1FcEn3Vu1pveCD3RKzPLYaQ6ge7EgG3E4y9JFSCZLEVNPp6gKvEjVyxih6Jo39jx8PFwi6FZ2y3JdP94xWrrwZo246UzNKcv7ZnM7nqGTsgFGrysWtdVFcWsANFHeu62wkX8MrAdpRwrrCmisBK2jNGvSbCw7zuAEwHCLg8G7UjsD7iuv3e

Public Key

1NifZwcKG5w2PzYmaXHGstHzkrxM7A923ZCswopNvxW: r5aXeKZ3pkA3nEtkSf7iqewhE5aAg39qbdqiVuJFcUnbaPKTjc3Fq3BArYb9My2RGZWEgrg67wuQ5PQ5QdASegsKoMhvG12Vxm52Vjmg2Wn1npkMKRkqAropwmC6iVgKfRKVjTZaV9yrUe86VWkQh5oaPr7FmaDN7bRiXvD5unsg76Q5z8iLXbdVAphQ2i3tDPZF8wp6rFLBumibxQeprrJULv6snNJDKF4W5i5CDMySZqe9M75m9qiP6kuXsGh4mjZ2z5Eok7mLBCydr8qspX8ZcMcQtZPiCtKBrx7EnPoBdPp6hBHmKv2sdU7i9VgAVwr1MrrYWUuqUMVdofce3xD5yssCEXV4ZKwSKKFKCBW1gNgTQ8PwUo7H1Xn7HKRYNvKjq82vNYn5qUAtwk828AbHnn87fC74LMJ

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