This is my gpn-mazing bot implementation from Gulasch-Programmier-Nacht 2022 (GPN 20), known from the michael-1.0 bot.
It uses some kind of depth-first search in the maze, with heuristics for finding the best decision at each crossing. In addition, it checks if the goal is even reachable via the unexplored-fields from the next field before going there, effectively skipping all areas which cannot lead to the goal anymore.
I also implemented cutting further unnecessary sub-trees from the depth-first search, based on missing improvement of the heuristic score, but it resulted in to many false-positives, i.e. skipping the correct path to the goal.
Compile and run with
cargo runThe program accepts one command line argument with the path of the config file.
If not given, a config.toml in the current working directory is expected.
An example config file is given in config.example.toml.
To enable logging, set the RUST_LOG environment variable to the desired log level (e.g. RUST_LOG=info).