run for gamma = 8 with
./run_safewithdrawal_08.py
- sets up variables to be optimized
- saves in a pickle file
- repeatedly calls safewithdrawal.py
- reduces learning rate each time
./safewithdrawal.py
learning_rate
steps
gamma
fileprefix
- loads variables from
fileprefix
.pickle - runs optimization using
gamma
andlearning_rate
until no improvement for specifiedsteps
- saves variables and csv files summarizing outcome
Safe Withdrawal with Certainty Equivalent Spending and Tensorflow Aug 2016.ipynb
- Jupyter notebook which allows you to run step by step, includes comments and graphs
- However running for a few hours in Jupyter not recommended, browser or Jupyter tends to hang
Please contact with any comments, pull requests
- Run efficiently on GPU
- Use better optimizer like AdamOptimizer instead of GradientDescentOptimizer
- adaptive learning rate (vs repeated calls with lower learning rate)
- momentum so less likely to get stuck.