CogitoNTNU/DeepTactics-Muzero
Feb 2025 – Mar 2025
2 Months active
Languages Used
Python
Technical Skills
Backend DevelopmentConfiguration ManagementDeep LearningMachine LearningRefactoringSoftware Design
Nicolai9897
PROFILE
Nicolai9897
Nicolai Olsen contributed backend improvements to the CogitoNTNU/DeepTactics-Muzero repository, focusing on enhancing code observability and correctness within the training loop. He implemented detailed logging for training losses, enabling tracking of total policy, reward, and value losses, and introduced optional aggregated loss outputs to support debugging and metric interpretation. Using Python and leveraging his skills in deep learning and debugging, Nicolai also addressed a duplicate calculation in the loss function, adding clarifying comments to improve maintainability and prevent future logging errors. His work strengthened the reliability and traceability of the training process, reflecting a thoughtful and methodical engineering approach.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
23Total
Bugs
4
Commits
23
Features
8
Lines of code
757
Activity Months2
Your Network
9 peopleWork History
March 2025
21 Commits • 6 Features
Mar 1, 2025March 2025 — CogitoNTNU/DeepTactics-Muzero monthly performance summary
21 Commits • 6 Features
Mar 1, 2025March 2025 — CogitoNTNU/DeepTactics-Muzero monthly performance summary
March 2025
February 2025
2 Commits • 2 Features
Feb 1, 2025February 2025 performance summary for CogitoNTNU/DeepTactics-Muzero: Delivered two core improvements to observability and configuration management that enable faster debugging, cleaner deployments, and more maintainable MuZero workflows. Implemented an introspection API to view trainable parameters across sub-networks and unified MuZero configuration into the main config with a renamed action_space_size. These changes reduce debugging time, minimize configuration drift, and improve cross-team collaboration.
February 2025
2 Commits • 2 Features
Feb 1, 2025February 2025 performance summary for CogitoNTNU/DeepTactics-Muzero: Delivered two core improvements to observability and configuration management that enable faster debugging, cleaner deployments, and more maintainable MuZero workflows. Implemented an introspection API to view trainable parameters across sub-networks and unified MuZero configuration into the main config with a renamed action_space_size. These changes reduce debugging time, minimize configuration drift, and improve cross-team collaboration.
Activity
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Quality Metrics
Correctness94.8%
Maintainability95.6%
Architecture86.0%
Performance86.0%
AI Usage22.6%
Skills & Technologies
Programming Languages
Python
Technical Skills
Algorithm ImplementationBackend DevelopmentCode CleanupCode ReadabilityCode RefactoringConfiguration ManagementDeep LearningDocumentationGame DevelopmentMCTSMachine LearningPyTorchPythonRefactoringSoftware Design
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