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EVOSEAL Roadmap

This document outlines the development roadmap for EVOSEAL, including planned features, improvements, and milestones.

🚀 Upcoming Features (Next 3-6 Months)

Core Engine Enhancements

  • [ ] Multi-objective Optimization
  • Support for optimizing multiple competing objectives simultaneously

  • Pareto front visualization and analysis tools

  • [ ] Enhanced Parallelization

  • Distributed computing support for large-scale evolutions

  • GPU acceleration for fitness evaluation

  • [ ] Advanced Selection Mechanisms

  • Tournament selection with configurable parameters
  • NSGA-II for multi-objective optimization
  • Novelty search integration

Model Integration

  • [ ] Expanded Model Support
  • Integration with local LLMs (Llama 2, Mistral, etc.)

  • Support for fine-tuning models on custom datasets

  • [ ] Model Ensembling

  • Combine multiple models for more robust code generation
  • Dynamic model selection based on task characteristics

Developer Experience

  • [ ] Improved CLI
  • Interactive shell for exploration
  • Better progress visualization

  • Enhanced logging and debugging tools

  • [ ] Jupyter Integration

  • Magic commands for interactive use

  • Visualization widgets for monitoring evolution

  • [ ] VSCode Extension

  • Visual interface for running evolutions
  • Integration with the editor's debugger

📅 Mid-term Goals (6-12 Months)

Performance Optimization

  • [ ] Incremental Evolution
  • Save and resume evolution state

  • Transfer learning between related tasks

  • [ ] Smart Initialization

  • Seed evolution with existing codebases
  • Template-based code generation

Advanced Features

  • [ ] Self-Improving Models
  • Automatic fine-tuning based on evolution results

  • Continuous learning from user feedback

  • [ ] Domain-Specific Optimizations

  • Specialized operators for common domains (web, data science, etc.)
  • Pre-built fitness functions for common tasks

Community & Ecosystem

  • [ ] Plugin System
  • Extensible architecture for custom operators

  • Community-contributed plugins

  • [ ] Model Zoo

  • Pre-trained models for common tasks
  • Sharing and discovery of successful evolutions

🌟 Long-term Vision (1+ Years)

Autonomous Development

  • [ ] Self-Hosting
  • Ability to improve its own codebase

  • Automated testing and deployment

  • [ ] Multi-Agent Collaboration

  • Teams of specialized agents working together
  • Distributed problem solving

Advanced Capabilities

  • [ ] Cross-Language Support
  • Evolution of code in multiple programming languages

  • Language translation between implementations

  • [ ] Formal Verification

  • Integration with formal methods
  • Proof generation for critical code paths

📊 Metrics & Success Criteria

  • Code Quality: Reduction in bugs and vulnerabilities in evolved code
  • Performance: Speedup in finding optimal solutions
  • Usability: Improved developer experience and satisfaction
  • Adoption: Growth in community contributions and integrations

🤝 Contributing

We welcome contributions to help achieve these goals! Please see our Contributing Guidelines for more information on how to get involved.

📝 License

This roadmap is licensed under the MIT License.

Last Updated: June 17, 2025

Last update: 2025-07-20
Created: 2025-06-17