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25 lines
1.5 KiB
Markdown
25 lines
1.5 KiB
Markdown
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# Progress Report for Week of April 2nd
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## Added Video Recording Capability to MinAtar environment
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You can now use the OpenAI Monitor Wrapper to watch the actions performed by agents in the MinAtar suite. (Currently the videos are in grayscale)
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Problems I had to solve:
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- How to represent the channels into a grayscale value
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- Getting the tensor into the right format (with shape and dtype)
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- Adding additional meta information that OpenAI expected
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## Progress Towards \#Exploration
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After getting nowhere trying to combine the paper on Random Network Distillation and Count-based exploration and Intrinsic Motivation, I turned the paper \#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning.
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This paper uses the idea of an autoencoder to learn a smaller latent state representation of the input. We can then use this smaller representation as a hash and count states based on these hashes.
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Playing around with the ideas of autoencoders, I wanted a way to discretized my hash more than just what floating point precision allows. Of course this turns it into a non-differential function which I then tried turning towards Evolutionary methods to solve. Sadly the rate of optimization was drastically diminished using the Evolutionary approach. Therefore, my experiments for this week failed.
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I'll probably look towards implementing what the paper did for my library and move on to a different piece.
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Guru Indian: 3140 Cowan Blvd, Fredericksburg, VA 22401
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