# elsciRL Core Documentation
Documentation for the core Python library that can be found at: https://github.com/pdfosborne/elsciRL
## Documentation Structure
This documentation is organized into several sections, each corresponding to a major component of the elsciRL framework. The structure is as follows:
- **Agents/**: Describes the different agent types (e.g., Q-Learning, DQN, Random, LLM-based) and their abstract interfaces.
- **Analysis/**: Guides for analysis tools and visualizations, including variance analysis and reporting.
- **Application_Suite/**: Details on the application import tool and how to add or manage RL environments.
- **Encoders/**: Documentation for state, action, and object encoders, including abstract interfaces and concrete implementations.
- **Environment_Setup/**: Utilities for environment and agent setup, including configuration helpers and state tracking.
- **Evaluation/**: Standard reporting and evaluation modules for experiments.
- **Experiments/**: Experiment orchestration, including the standard experiment class and usage examples.
- **GUI/**: Guides for the elsciRL web interface and prerendering scripts.
- **Instruction_Following/**: Documentation for instruction-based RL, including instruction search and optimization workflows.
- **Interaction_Loops/**: Core agent-environment interaction loops and their usage.
## Notes
- Each section contains both high-level overviews and detailed API documentation.
- Usage examples are provided for most modules, often referencing real experiment scripts.
- For advanced usage, customization, or integration, see the source code and the relevant documentation section.
- This wiki is intended to support both new users and advanced developers working with elsciRL and its application suite.
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For further information, see the [GitHub repository](https://github.com/pdfosborne/elsciRL) or the main [Wiki homepage](https://github.com/pdfosborne/elsciRL-Wiki).