Metadata-Version: 2.1
Name: llfo
Version: 0.1.0
Summary: Lifelong Learning in Flexible Ontologies Framework
License: MIT
Author: Your Name
Author-email: you@example.com
Requires-Python: >=3.8,<4.0
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: gymnasium (>=0.26.0)
Requires-Dist: matplotlib (>=3.4.0)
Requires-Dist: numpy (>=1.21.0)
Requires-Dist: pandas (>=1.3.0)
Requires-Dist: torch (>=1.10.0)
Project-URL: Bug Tracker, https://github.com/yourusername/llfo/issues
Project-URL: Documentation, https://llfo.readthedocs.io/
Project-URL: Homepage, https://github.com/yourusername/llfo
Project-URL: Repository, https://github.com/yourusername/llfo.git
Description-Content-Type: text/markdown

# LLFO - Lifelong Learning in Flexible Ontologies

A Python package implementing lifelong learning algorithms with flexible ontological structures.

## Theory

LLFO combines lifelong learning with flexible ontological structures to enable continuous knowledge acquisition and adaptation. Key concepts include:

### Flexible Ontologies
- Dynamic knowledge representation through adaptable concept hierarchies
- Automatic restructuring of relationships between concepts
- Probabilistic edge weights between ontological nodes

### Lifelong Learning Components
- Knowledge retention through experience replay
- Forward transfer to new tasks
- Backward transfer to improve previous knowledge
- Catastrophic forgetting prevention

### Learning Mechanisms
- Ontology structure learning
- Parameter learning within nodes
- Relationship weight adaptation
- Task-specific adaptation

## Installation

```bash
pip install -e .
```

## Usage

```python
import llfo

# Example code coming soon
```

## License

MIT

