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License: MIT License
Policy-based optimization : single-step policy gradient seen as an evolution strategy
License: MIT License
Hello, it's really a nice job!
Currently, I tried to use this improved method to do some fluid optimization work. But while reading the code, I found that for every examples in /envs folder, the observation self.obs returned seems to be zeroes. I also checked this in the previous repository drl_shape_optimization, but found no clear definition in both papers and codes.
I know the observation put inito the network should be the same for every generation. But is it ok to set this variable simply to be zeroes? Or in other words, is it possible to feed the network some other values which relate to the environment so that it can do optimization in other conditions (e.g. the observation could be Re or inflow direction in drl_shape_optimization)
Looking forward to your reply!
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