Thanks for the response Satchel! We create a 2D matrix representing the square board, bordered by values of 0.8, and represent the agent with 0.1, and the agent’s previous location with 0.2. All other locations are 0. There are some other values I’d like to include in the grid eventually, but right now I’m trying to get a basic sample working. The 2D matrix is flattened prior to input.
I’ve tried learning rates ranging from 0.01 and 0.0001, and currently use 0.99 for the discount factor. I can try experimenting with other values.
However, I think your suggestion of amount of data per update is interesting. Since the agent dies a lot at first, most of the episodes are only 1-4 moves in length. Currently, the update is done at the end of every episode. It sounds like this might be way too frequent, so I’ll try increasing this.