Collect Feedback and Implement Improvements for ARTIST Integration

.gitignore

@@ -278,3 +278,7 @@ mypy_typing_report.txt
 ruff_typing_report.json
 ruff-baseline.txt
 pnpm-lock.yaml
+
+# MCP servers for VS Code extensions
+browser-tools-mcp/
+fetch-mcp/

artist_experiments/README.md

@@ -88,3 +88,17 @@ See `requirements-artist.txt` for the complete list of dependencies.
 - [ARTIST Framework Summary](../docs/research/artist_framework_summary.md)
 - [ARTIST Framework Pilot Use Cases](../docs/research/artist_framework_pilot_use_cases.md)
 - [ARTIST Framework Implementation Recommendations](../docs/research/artist_framework_implementation_recommendations.md)
+
+## Feedback & Iterative Improvements
+
+### Summary of Feedback
+Feedback from users and developers on ARTIST agent usability and performance has highlighted the agent's effectiveness in mathematical reasoning tasks, with reinforcement learning (RL) notably improving multi-step problem solving. However, suggestions were made to provide clearer error messages and to expand the range of supported tools. Additionally, while RL training contributed to better performance, feedback indicated a need for more real-world evaluation scenarios to assess robustness and utility.
+
+### Iterative Improvements (Made or Planned)
+- Improved error handling and clearer error messages
+- Expanded the tool registry to cover a broader set of user needs
+- Enhanced RL reward functions for more meaningful learning signals
+- Designed and integrated more realistic and diverse test cases
+- Ongoing collection and analysis of user/developer feedback to guide further enhancements
+
+*This section will be updated as more feedback is gathered and additional improvements are implemented.*

docs_source/source/artist_experiments.rst

@@ -0,0 +1,13 @@
+ARTIST Experiments
+==================
+
+The ARTIST (Agentic Reasoning and Tool Integration in Self-improving Transformers) experiments demonstrate advanced agentic reasoning, reinforcement learning, and dynamic tool integration for LLMs.
+
+- For setup instructions, detailed experiment descriptions, and dependencies, see the full [ARTIST Experiments README](../../artist_experiments/README.md).
+- Recent updates include a 'Feedback & Iterative Improvements' section that documents user/developer feedback and tracks ongoing enhancements to the ARTIST agent logic, tool coverage, and RL training.
+
+Key experiments:
+- Enhanced Mathematical Problem-Solving (RL for multi-step math)
+- Multi-API Orchestration for Market Research
+
+Feedback and improvement history are maintained transparently in the ARTIST Experiments README for review by users and contributors.

docs_source/source/index.rst

@@ -11,6 +11,7 @@ python -m pAIssive_income
    overview
    getting_started
    examples
+   artist_experiments
    api/index
    contributing
    changelog