Support SciPy sparse matrices for alpharank code, implement Stochasically Stable Distributions#1404
Support SciPy sparse matrices for alpharank code, implement Stochasically Stable Distributions#1404l-ouis wants to merge 1 commit into
Conversation
|
Thanks for your pull request! It looks like this may be your first contribution to a Google open source project. Before we can look at your pull request, you'll need to sign a Contributor License Agreement (CLA). View this failed invocation of the CLA check for more information. For the most up to date status, view the checks section at the bottom of the pull request. |
|
Thanks @l-ouis ! Can you sign the CLA? |
There was a problem hiding this comment.
Can you fix the indentation to be consistent? (two-space indent)
E.g kosaraju.py appears to use 4-space indent but there might be others.|
Edit: original_ssd.py as well. Or maybe you don't intend to keep that one in the PR? (i.e. is it the original implementation that you're fitting into OpenSpiel, for instance)
adcf5f8 to
961944b
Compare
|
Fixed indentation / moved kosaraju logic into ssd.py. Also implemented more correct sparsity logic to the ssd portion. |
Evolutionary dynamic Markov chains are sparse matrices, so using SciPy sparse matrices and operations can save memory.
Also implements SSD: https://arxiv.org/pdf/1207.1424, which is an exact algorithm that computes the stochastically stable distribution of a Markov chain (and can be used similarly as alpharank)
@Eric-Ewing