Open Source AI Project


DarkForest is an open-source Go engine developed by Facebook Research, featuring a Monte Carlo Tree Search (MCTS) engine and a trained Deep Convolutional Neural Networ...


DarkForest is a groundbreaking project developed by Facebook Research, designed to push the boundaries of artificial intelligence in the game of Go. At its core, it incorporates a sophisticated Monte Carlo Tree Search (MCTS) engine paired with a Deep Convolutional Neural Network (DCNN) model. This combination allows DarkForest to exhibit an exceptional level of play, with the DCNN model alone, even without the search component, reaching a rank of approximately KGS 3D. This ranking places it among the upper echelons of Go playing capabilities, especially impressive for a model operating without the intricate search algorithms typically necessary for such high levels of play.

The project is not just about competing at Go; it’s also a platform for research and development in the field of computer Go and deep learning. The inclusion of a playout model and the promise of future training code releases highlight its role as a resource for those interested in exploring the intricacies of AI and machine learning within this ancient game. DarkForest’s journey began in May of the previous year, showcasing a narrative of dedication and perseverance. From its initial stages of visual research with minimal resources, the project has encountered a variety of challenges, including periods of intense work, setbacks, and a rollercoaster of emotions tied to significant milestones in the Go community.

Despite these challenges, DarkForest has achieved substantial recognition within a short period. After becoming open-source, it quickly garnered over a thousand stars on GitHub, along with numerous forks and watches, indicating a strong interest and endorsement from the developer and research communities. This acclaim is not just a testament to its technical achievements but also to its potential as a tool and resource for further exploration in the field.

Written in pure C for initial convenience, there’s an ongoing consideration to refactor the codebase to C++11. This potential transition reflects a commitment to not only maintaining but also enhancing the project’s robustness, efficiency, and accessibility to contributors. The move towards C++11 could open up new avenues for development, leveraging modern programming features and practices to improve the project’s overall structure and performance.

In summary, DarkForest stands as a pioneering effort at the intersection of gaming, artificial intelligence, and deep learning research. Its purpose extends beyond merely creating a competitive Go engine; it seeks to advance understanding, foster innovation, and provide a valuable resource for the research community. Through its impressive technical features, notable achievements, and ongoing development, DarkForest exemplifies the potential of collaborative, open-source projects to drive forward the frontiers of technology and knowledge.

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