Learning-Robust-Options-by-Conditional-Value-at-Risk-Optimization

(★ 11)

Source files to replicate experiments in my NeurIPS 2019 paper.

File Explorer

  • .gitignore
  • EvalAverageCVaR.py
  • EvalAverageReturn.py
  • GeneratebestpolTextMaxAverageReturn.py
  • GeneratebestpolTextMaxAverageReturnwithCVaRThreth.py
  • LICENSE
  • README.md
  • robustoption20190919.yml
  • run_test_w_best_cvar_pol.sh
  • run_test_w_specified_epoch.sh
  • runexp.sh
  • Scores4EachParameterPerturbation.py

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Commands referenced in this DOCs, explained below.

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conda env

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conda env create {{[-f|--file]}} {{path/to/file}}

Create an environment from an environment file (YAML, TXT, etc.):

conda env remove {{[-n|--name]}} {{environment_name}}

Delete an environment and everything in it:

conda env update {{[-f|--file]}} {{path/to/file}} --prune

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python

Start a REPL (interactive shell):

python {{path/to/file.py}}

Execute a specific Python file:

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Execute a specific Python file and start a REPL:

// repository documentation