instadeepai/Mava
Jul 2025 – Jul 2025
1 Month active
Languages Used
JAXPython
Technical Skills
Configuration ManagementFlaxGraph Neural NetworksJAXJraphMulti-Agent Reinforcement Learning
Joseph Daniel Selvaraaj
PROFILE
Joseph Daniel Selvaraaj
Worked on expanding the Mava framework by introducing graph-based observations and integrating graph neural networks to enhance multi-agent modeling and environment representation. Developed a dedicated graph-first extension that maintained compatibility with existing components, allowing researchers to experiment with relational architectures and graph-structured interactions. Implemented new GNN network components and wrappers for graph-based environments, updating core networks and utilities to support these advanced representations. The work, contributed to the instadeepai/Mava repository, leveraged JAX, Flax, and Jraph, and established a foundation for more sophisticated multi-agent reasoning and analysis through graph structures, focusing on robust configuration management and wrapper design.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,019
Activity Months1
Work History
July 2025
1 Commits • 1 Features
Jul 1, 2025Monthly summary for 2025-07 focused on expanding Mava with graph-based observations and GNN integration to enhance multi-agent modeling and environment representations. Delivered a dedicated graph-first extension while maintaining compatibility with existing components, enabling researchers to experiment with relational architectures and graph-structured interactions.
1 Commits • 1 Features
Jul 1, 2025Monthly summary for 2025-07 focused on expanding Mava with graph-based observations and GNN integration to enhance multi-agent modeling and environment representations. Delivered a dedicated graph-first extension while maintaining compatibility with existing components, enabling researchers to experiment with relational architectures and graph-structured interactions.
July 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture100.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JAXPython
Technical Skills
Configuration ManagementFlaxGraph Neural NetworksJAXJraphMulti-Agent Reinforcement LearningWrapper Design
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