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...The repository includes training code, model checkpoints, and infrastructure for both language modelling (via the ParlAI framework) and reinforcement learning for strategy agents. It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. Configuration is managed via protobuf files to define tasks such as self-play, benchmark agent comparisons, and RL training. The project is now archived and read-only, reflecting that it is no longer actively developed but remains publicly available for research use.

project created on: 2013.05.25 bitbucket repo: http://bit.ly/pyminesweeper_bitbucket Simple minesweeper game in python CONTROLS: Right Click - "flag" the box; also start next game Left Click - reveal empty box(es) or mine Based on the game "Memory Puzzle" from pygame tutorial http://inventwithpython.com/pygame/chapter3.html UPDATE 1.2 (05.11.2015): Major code refactoring UPDATE 1.3 (06.09.2015): Bugfixes; Minor code refactoring # README # In order to run minesweeper you need to install PyGame http://pygame.org/download.shtml Easy way is to install it via wheel, see e.g. http://stackoverflow.com/a/28127864 If 64-bit wheel (.whl) package installation fails, try its 32-bit version. You can also find .msi installation package on their bitbucket repo. https://bitbucket.org/pygame/pygame/downloads Contact me at herman.yanush3@gmail.com