catastrophic forgetting

[Daniel Shawul]

A less complex problem is to train one neural network for the same game but on different board sizes. This has been done for Go which is played on board sizes of 9x9, 13x13, and 19x19. This paper https://arxiv.org/abs/1902.10565 uses an input plane mask to indicate on-board locations. They go further than that and apply the mask after each convolution step and similar operations. I am gonna first try and see if providing the mask suffices.

@chris The subject of transfer learning is very interesting because it generalizes learning to other similar domains than what it is orignally trained for.
I think the gist of the Deepmind paper is to figure out important weights for playing a game and slow down learning rate for them so that they are not forgotten quickly.

[AlvaroBegue]

Is training for all the variants at the same time an option? I mean, have each minibatch contain examples from each of the variants.