I decided to start learning neural networks by creating a bot for the game. One of the intermediate steps is to create a global map from a series of inaccurate overlapping sub-maps. This task can be solved using OpenCV, but this solution will be too limited and sensitive (in the future I intend to complicate the task and work directly with the map image, instead of binary masks).
I've tried the following options:
predict the position of a new map area within the global map. (as a probability distribution)
predict the new state of the global map from the old and new minimap.
I've tried a lot of options formulation of the problem of network architecture, including the idea of conjoined networks, but nothing gave any relevant results.
Some articles about solving similar problems:
Here is an example of one of the options statement of the problem: