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Design & Architecture
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Actor-Critic Architecture
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Input & Action Spaces
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Reinforcement Learning Algorithm
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Reward Function & Observation Space
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API Reference
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Brittle Star Environment
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Training Models
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<h1 id="documentation">Documentation</h1>
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<p>Welcome to the Brittle Star project documentation. This codebase contains the implementations and research for the scientific evaluation of controller modularity in brittle-star-like robots trained using Reinforcement Learning.</p>
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<p>For the core codebase, scripts, and contribution history, visit our <a href="https://github.com/SELab-3-2026/SEL3-2026-Groep-4">GitHub Repository</a>.</p>
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<h2 id="core-requirements-guides">Core Requirements & Guides</h2>
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<ul>
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<li><strong><a href="DEVELOPMENT/">Installation Instructions</a></strong>: Steps to set up your development environment locally or in a devcontainer using <code>uv</code>, including GPU configuration. For High-Performance Computing (HPC) setup details, see the <strong><a href="HPC/">HPC Guide</a></strong>.</li>
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<li><strong><a href="api/training/">How to Run Experiments</a></strong>: A complete guide on running training jobs, setting custom hyperparameters, and overriding config options using Hydra.</li>
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<li><strong><a href="api/reproduction/">Results & Reproduction</a></strong>: Guide on how to access our public WandB training runs table and reproduce our training and evaluation phases (determining the best checkpoint vs. comparing architectures).</li>
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<li><strong><a href="CONTRIBUTING/">Contribution Guidelines</a></strong>: Standards, rules, and best practices for developing and adding code to the repository.</li>
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<h2 id="repository-structure">Repository Structure</h2>
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<div class="highlight"><pre><span></span><code>.
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├── configs/ # Hydra configuration files (YAML)
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├── docs/ # Comprehensive documentation and API guides
|
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├── runs/ # Default output directory for Hydra and training artifacts
|
|
├── scripts/ # High-level entrypoints for training, simulation, and evaluation
|
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├── src/
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│ ├── brittle_star_project/ # Core library and environment logic
|
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│ │ ├── evaluation/ # Checkpoint evaluation, rollout logic, and metrics persistence
|
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│ │ └── trainers/ # Training loop implementations (e.g., PPO)
|
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│ └── experiment_logger/ # Standalone logging package
|
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└── tests/ # Unit and integration tests
|
|
</code></pre></div>
|
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<h2 id="design-architecture-design">Design & architecture (<code>/design</code>)</h2>
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<p>If you are interested in the "why did you do it like this?"</p>
|
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<ul>
|
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<li><a href="design/actor-critic/">Actor-Critic Architecture</a>: Description of the actor-critic pipeline.</li>
|
|
<li><a href="design/communication/">Communication Scheme</a>: Message propagation, Nerve-Net style.</li>
|
|
<li><a href="design/controllers/">Modularity & Topology</a>: Macroscopic brain topology, centralized, arm-level, segment-level.</li>
|
|
<li><a href="design/input_action_spaces/">Input & Action Spaces</a>: Description of the model's input and output.</li>
|
|
<li><a href="design/learning_algorithm/">Reinforcement Learning Algorithm</a>: RL techniques, i.e. PPO.</li>
|
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<li><a href="design/reward_function/">Reward Function & Observation Space</a>: Goals, fitness tracking, and reward structures.</li>
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</ul>
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<h2 id="api-reference-api">API reference (<code>/api</code>)</h2>
|
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<p>If you are interested in the "how do I use it?"</p>
|
|
<ul>
|
|
<li><a href="api/environment/">Brittle Star Environment</a>: MuJoCo environment interaction and configuration.</li>
|
|
<li><a href="api/training/">Training Models</a>: How to configure and run experiments.</li>
|
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<li><a href="api/tracking/">Tracking & Monitoring</a>: Setting up WandB and TensorBoard to monitor runs.</li>
|
|
<li><a href="api/evaluation/">Checkpoint & Model Evaluation</a>: Evaluating checkpoints and comparing fault tolerance.</li>
|
|
<li><a href="api/simulation/">Interactive Simulation & Visualization</a>: Visualizing models in the MuJoCo viewer or rendering simulation videos.</li>
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<li><a href="api/analysis/">Analysis & Plotting Tools</a>: Comparing checkpoints and generating plots.</li>
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<li><a href="api/reproduction/">Results & Reproduction</a>: Accessing WandB results and running reproduction pipelines.</li>
|
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</ul>
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