Metta-AI/metta
Aug 2025 – Aug 2025
1 Month active
Languages Used
C++PythonTypeScriptYAML
Technical Skills
Action HandlingAgent SimulationAgent-Based ModelingC++C++ DevelopmentConfiguration Management
gregsoftmax
PROFILE
Gregsoftmax
Worked on the Metta-AI/metta repository to enhance multi-agent simulation capabilities by implementing robust 8-way movement and orientation handling, including obstacle-aware fallback and configurable agent interference. Developed new agent interaction dynamics using YAML-based autocurricula, allowing flexible configuration of agent behaviors and interactions. Introduced a box object to the Mettagrid environment, supporting resource placement and retrieval actions with resource consumption and ownership tracking. Added a probabilistic resource loss mechanism configurable per timestep, with comprehensive tests to ensure reliability. Leveraged C++, Python, and YAML for development, focusing on action handling, agent-based modeling, and rigorous unit testing to drive simulation reliability.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
4
Lines of code
1,558
Activity Months1
Your Network
43 peopleSame Organization
@stem.ai6
Brandon HarveyMember
Dhaya LakshminarayananMember
Gabriel KeithMember
Jack HeartMember
Joshua SeimsMember
S. Alex SmithMember
Shared Repositories
37
Axel KerbecMember
al-doesMember
Brandon HarveyMember
daphnedemekasMember
David BloominMember
Dhaya LakshminarayananMember
Dominik FarrMember
Gabriel KeithMember
George DeaneMember
Work History
August 2025
5 Commits • 4 Features
Aug 1, 2025August 2025 monthly summary for Metta-AI/metta focused on delivering robust navigation, configurable agent interactions, and new resource-management capabilities, with tests driving reliability and business value for multi-agent simulations.
5 Commits • 4 Features
Aug 1, 2025August 2025 monthly summary for Metta-AI/metta focused on delivering robust navigation, configurable agent interactions, and new resource-management capabilities, with tests driving reliability and business value for multi-agent simulations.
August 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability84.0%
Architecture84.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++PythonTypeScriptYAML
Technical Skills
Action HandlingAgent SimulationAgent-Based ModelingC++C++ DevelopmentConfiguration ManagementEnvironment ConfigurationGame DevelopmentObject-Oriented ProgrammingPathfindingPythonPython DevelopmentReinforcement LearningTestingUnit Testing
Repositories Contributed To
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