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[Illinois]: Perturbative Reinforcement Learning Using Directed Drift
This tool trains two-layered networks of sigmoidal units to associate patterns using a real-valued adaptation of the directed drift algorithm.
From Tutorial on Neural Systems Modeling, Chapter 7:
In the directed drift algorithm (Venkatesh 1993), input patterns are presented to the network, and one or several randomly chosen weights have their binary values flipped if the output is in error, but the weights are left unperturbed otherwise. Directed drift is proven to work in this restricted context (Venkatesh 1993). We explore its use for real-valued weights in the next example.
Researchers should cite this work as follows:
- Tutorial on Neural Systems Modeling, Copyright 2010 Sinauer Associates Inc. Author: Thomas J. Anastasio