
Worked on the GamesmanClassic repository to overhaul game position encoding, incorporating player turn information and simplifying the hashing and unhashing logic to improve correctness and maintainability. Addressed edge cases in move generation and input parsing, particularly for boards with multiple blank spaces, reducing the risk of illegal moves and enhancing reliability. Utilized C programming, algorithm design, and data structures to refactor core components, laying a foundation for future AI and performance enhancements. The work focused on robust algorithm implementation under real-game constraints, ensuring that the codebase is better structured for ongoing development and easier integration of advanced features.
November 2024 performance summary for GamesmanClassic: Delivered a major state-encoding overhaul and robust move generation, improving correctness, maintainability, and groundwork for future enhancements. Key outcomes include an encoding overhaul that incorporates player turn and simplified hashing/unhashing, and fixes to move generation and input parsing handling edge cases such as multiple blank spaces. These changes reduce risk of illegal moves, improve reliability, and lay groundwork for future AI and performance optimizations. Demonstrated strong skills in refactoring, algorithmic thinking, and debugging under real-game constraints.
November 2024 performance summary for GamesmanClassic: Delivered a major state-encoding overhaul and robust move generation, improving correctness, maintainability, and groundwork for future enhancements. Key outcomes include an encoding overhaul that incorporates player turn and simplified hashing/unhashing, and fixes to move generation and input parsing handling edge cases such as multiple blank spaces. These changes reduce risk of illegal moves, improve reliability, and lay groundwork for future AI and performance optimizations. Demonstrated strong skills in refactoring, algorithmic thinking, and debugging under real-game constraints.

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