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Add Progressive Reinforcement Capabilities (potentially via Q-Learning) #289

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levinwil opened this issue Oct 8, 2020 · 3 comments
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@levinwil
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levinwil commented Oct 8, 2020

Is your feature request related to a problem? Please describe.
We would like to devise a Reinforcement approach that leverages progressive learning to improve its in-task predictions in mapping states to actions.

Describe the solution you'd like
Treat Q-Learning as a classification problem (where a network or forest replaces the state to action map) and continue as normal.

Here's a tutorial for Q-Learning in Keras for reference: https://keras.io/examples/rl/deep_q_network_breakout/

Describe alternatives you've considered
None considered, but there are potentially more reinforcement learning approaches we could try

@sparthib
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I am interested in this issue. @javierhow is willing to help.

@PSSF23 PSSF23 added this to Code (To Do) [Sprint 1] in ProgLearn Aug 24, 2021
@PSSF23 PSSF23 added the ndd Neuro Data Design label Aug 24, 2021
@shoulton
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shoulton commented Oct 7, 2021

I'm interested in this issue if it's available

@mordred-skywalker
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I'm also interested in the issue.

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