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CEREBRUM - Changelog

All notable changes to the CEREBRUM module will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[0.1.0] - 2026-01-05​

Added​

  • Initial implementation of CEREBRUM module
  • Case-based reasoning with Case, CaseBase, and CaseRetriever classes
  • Bayesian inference with BayesianNetwork and InferenceEngine
  • Active inference with ActiveInferenceAgent based on free energy principle
  • Model transformation with AdaptationTransformer and LearningTransformer
  • Visualization tools for networks, cases, and inference results
  • Core CerebrumEngine orchestrator
  • Comprehensive documentation (README, AGENTS, SPEC, API, Usage Examples)
  • MCP tool specifications
  • Unit and integration test structure

Features​

  • Case similarity computation (Euclidean, cosine)
  • Multiple Bayesian inference methods (variable elimination, MCMC)
  • Case weighting strategies (distance, frequency, hybrid)
  • Model adaptation and learning from feedback
  • Integration with other codomyrmex modules

Dependencies​

  • numpy: Numerical computations
  • scipy: Statistical functions
  • networkx: Graph structures
  • scikit-learn: Similarity metrics (optional)
  • matplotlib: Visualization (optional)

Detailed Architecture and Implementation​

Design Principles​

  1. Strict Modularity: Each component is isolated and communicates via well-defined APIs.
  2. Performance Optimization: Implementation leverages lazy loading and intelligent caching to minimize resource overhead.
  3. Error Resilience: Robust exception handling ensures system stability even under unexpected conditions.
  4. Extensibility: The architecture is designed to accommodate future enhancements without breaking existing contracts.

Technical Implementation​

The codebase utilizes modern Python features (version 3.10+) to provide a clean, type-safe API. Interaction patterns are documented in the corresponding AGENTS.md and SPEC.md files, ensuring that both human developers and automated agents can effectively utilize these capabilities.