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Model from Tsuda B, Richmond BJ, Sejnowski TJ. Exploring strategy differences between humans and monkeys with recurrent neural networks.

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humanVmonkey

Model from:
Tsuda B, Richmond BJ, Sejnowski TJ. Exploring strategy differences between humans and monkeys with recurrent neural networks.

rnn_model.py contains recurrent neural network model trained by reinforcement learning.

humanVmonkey_env.py contains the specifications for the three working memory tasks from Wittig et al. 2016 (http://learnmem.cshlp.org/content/23/11/644).

Organization of rnn_model.py is

  • helper fxns
  • definition of network class
  • definition of worker class
    • train fxn
    • get_experience fxn
    • test fxn
  • main
    • definition of parameters and output directories
    • creation of central network
    • creation of worker objects that run the network
    • script to deploy workers for training AND testing

Command to run rnn_model.py:
python3 rnn_model.py [NETSZ] [EPS_TO_TRAIN_ON] [PERFTHRESH] [RUNNO] [GPU]

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Model from Tsuda B, Richmond BJ, Sejnowski TJ. Exploring strategy differences between humans and monkeys with recurrent neural networks.

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