---
name: Feature Request
description: Request new features or enhancements for plume_nav_sim reinforcement learning environment
title: "[FEATURE] Brief description of the requested feature"
labels: ["enhancement", "feature-request", "needs-triage"]
assignees: []
---

## Feature Request for plume_nav_sim

**Thank you for contributing to the plume navigation research community!** 🔬

This template helps you request new features, enhancements, or improvements to the plume_nav_sim Gymnasium environment. Please provide detailed information to help maintainers understand your research needs and implementation requirements.

<!-- Your feature request helps advance reinforcement learning research and supports the scientific community -->

### Feature Category

Select the primary category for this feature request:

- [ ] Environment API Enhancement (new methods, improved interfaces)
- [ ] Plume Model Extensions (dynamic plumes, new distributions, multi-source)
- [ ] Rendering and Visualization (new modes, interactive features, animation)
- [ ] Performance Optimization (speed improvements, memory efficiency)
- [ ] Action and Observation Space Extensions (continuous actions, multi-dimensional observations)
- [ ] Reward System Enhancements (new reward functions, multi-objective rewards)
- [ ] Seeding and Reproducibility Improvements (enhanced determinism, cross-platform consistency)
- [ ] Testing and Validation Tools (benchmarking, validation scripts, debugging)
- [ ] Multi-Agent Support (concurrent agents, coordination mechanisms)
- [ ] Integration and Compatibility (new frameworks, export formats, data logging)
- [ ] Documentation and Examples (tutorials, advanced usage, research guides)
- [ ] Configuration and Customization (parameter management, environment variants)
- [ ] Research Tools and Analytics (data collection, analysis utilities, metrics)
- [ ] Other (please specify in description)

### Target Development Phase

When should this feature be implemented based on project roadmap?

- [ ] Proof-of-Life (PoL) - Critical for basic functionality
- [ ] Research Scale - Important for scientific research applications
- [ ] Production Scale - Advanced features for production deployments
- [ ] Future Consideration - Innovative ideas for long-term development
- [ ] Not Sure - Need guidance on appropriate development phase

### Feature Description

**Provide a clear and comprehensive description of the requested feature:**

```
Describe the feature in detail:
- What functionality should be added?
- How would it work?
- What are the key components or changes needed?
- How would users interact with this feature?
```

### Research Motivation and Use Case

**Explain why this feature is needed for reinforcement learning research:**

```
Research context:
- What research problem does this address?
- How would this feature advance plume navigation research?
- What specific experiments or studies would benefit?
- Are there related research papers or methodologies?
- How does this fit into the broader RL research ecosystem?
```

### Proposed Implementation Approach (Optional)

**Technical implementation suggestions:**

```python
# Implementation ideas:
# - Architectural changes needed
# - New classes, methods, or modules
# - Integration points with existing code
# - Dependencies or external libraries
# - Backward compatibility considerations
# - Performance implications
```

### Usage Example (Optional)

**Show how you would use this feature with code examples:**

```python
import gymnasium as gym
import plume_nav_sim

# Example of how the new feature would be used
env = gym.make('PlumeNav-YourFeature-v0')
obs, info = env.reset()

# Your feature usage example here
result = env.your_new_feature(params)
print(f'Feature result: {result}')
```

### Feature Impact Assessment

**Select all areas that this feature would impact:**

- [ ] Environment API (reset, step, render, close methods)
- [ ] Action and Observation Spaces
- [ ] Plume Model and Concentration Calculations
- [ ] Rendering and Visualization System
- [ ] State Management and Episode Handling
- [ ] Reward System and Termination Logic
- [ ] Seeding and Reproducibility Mechanisms
- [ ] Performance and Memory Usage
- [ ] Testing Framework and Validation
- [ ] Documentation and Examples
- [ ] Backward Compatibility
- [ ] Integration with External Tools
- [ ] Configuration and Parameter Management

### Implementation Complexity

**Estimate the complexity of implementing this feature:**

- [ ] Low - Simple enhancement or parameter addition
- [ ] Medium - New functionality requiring moderate changes
- [ ] High - Complex feature requiring significant architectural changes
- [ ] Very High - Major feature requiring substantial development effort
- [ ] Unknown - Need technical analysis to determine complexity

### Priority Level

**How important is this feature for your research or use case?**

- [ ] Critical - Blocking research or essential functionality
- [ ] High - Significantly improves research capabilities
- [ ] Medium - Useful enhancement that would be beneficial
- [ ] Low - Nice-to-have improvement
- [ ] Enhancement - Quality of life or convenience improvement

### Performance Considerations (Optional)

**How might this feature impact performance?**

```
Performance impact considerations:
- Should maintain <1ms step execution
- May increase memory usage by ~X MB
- Requires optimization for large grid sizes
- Expected rendering performance impact: <5ms RGB, <50ms human
```

### Compatibility Requirements

**Select compatibility considerations for this feature:**

- [ ] Must maintain Gymnasium API compliance
- [ ] Should work across all supported Python versions (3.10-3.13)
- [ ] Must support both rgb_array and human rendering modes
- [ ] Should maintain backward compatibility with existing code
- [ ] Must preserve reproducibility and seeding behavior
- [ ] Should work on Linux, macOS, and Windows (limited)
- [ ] Must integrate with existing test suite
- [ ] Should follow established performance targets
- [ ] Must maintain scientific accuracy and research standards

### Alternatives Considered (Optional)

**Have you considered alternative approaches or workarounds?**

```
Alternative solutions:
- Other ways to achieve similar functionality
- Existing tools or libraries that might provide this
- Workarounds you've tried
- Why this specific approach is preferred
```

### Related Issues or Pull Requests (Optional)

**Link any related issues, discussions, or pull requests:**

```
Related references:
- Related to #123
- Builds on #456
- Discussed in #789
```

### Testing and Validation Considerations (Optional)

**How should this feature be tested and validated?**

```
Testing requirements:
- Unit tests needed
- Integration test scenarios
- Performance benchmarks
- Reproducibility validation
- Manual testing steps
- Example validation
```

### Documentation Requirements

**What documentation would be needed for this feature?**

- [ ] API documentation and docstrings
- [ ] Usage examples and tutorials
- [ ] Performance benchmarking documentation
- [ ] Integration guide with existing code
- [ ] Research methodology and scientific background
- [ ] Troubleshooting and common issues guide
- [ ] Migration guide for breaking changes
- [ ] Advanced usage patterns and best practices

### Additional Context and Resources (Optional)

**Any additional information that would help implement this feature:**

```
Additional context:
- Research papers or references
- Similar implementations in other libraries
- Screenshots, diagrams, or mockups
- Community discussions or feedback
- Timeline constraints or deadlines
- Available resources for implementation
```

### Contribution Readiness

**Are you interested in contributing to the implementation?**

- [ ] I would like to implement this feature myself
- [ ] I can provide technical guidance and domain expertise
- [ ] I can help with testing and validation
- [ ] I can contribute documentation and examples
- [ ] I can provide research context and use case validation
- [ ] I would like to collaborate with other contributors
- [ ] I prefer to leave implementation to maintainers

---

## For Maintainers

**Triage Checklist:**
- [ ] Feature category and scope clearly defined
- [ ] Research motivation and use case validated
- [ ] Implementation complexity assessed
- [ ] Performance impact evaluated
- [ ] Compatibility requirements reviewed
- [ ] Development phase alignment confirmed
- [ ] Resource requirements estimated
- [ ] Community interest and support evaluated

**Implementation Planning:**
- [ ] Technical approach reviewed and approved
- [ ] API design considerations addressed
- [ ] Performance benchmarking plan established
- [ ] Testing strategy defined
- [ ] Documentation requirements specified
- [ ] Breaking change impact assessed
- [ ] Integration with existing codebase planned

**Priority Assignment:**
- [ ] Critical: Essential for core functionality (implement immediately)
- [ ] High: Significant research value (next development cycle)
- [ ] Medium: Valuable enhancement (planned development)
- [ ] Low: Quality of life improvement (future consideration)
- [ ] Research: Experimental feature (R&D phase)

**Development Phase Alignment:**
- [ ] Proof-of-Life: Fits current minimal viable implementation
- [ ] Research Scale: Appropriate for research-focused development
- [ ] Production Scale: Suitable for production deployment features
- [ ] Future: Innovative concept requiring longer-term planning
