Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models

Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models. Say, B. & Sanner, S. Artificial Intelligence Journal (AIJ), 285:103291, August, 2020.

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@article{sanner:aij20,
  author = {Buser Say and Scott Sanner},
  title = {Compact and Efficient Encodings for Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models},
  year = {2020},
  volume = {285},
  pages = {103291},
  month = {August},
  year = {2020},
  journal = "Artificial Intelligence Journal ({AIJ})",
  url_paper = {https://doi.org/10.1016/j.artint.2020.103291},
  url_arxiv = {https://arxiv.org/abs/1811.10433}
}

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