
TensorForce: A TensorFlow library for applied reinforcement learning - k_f
https://reinforce.io/blog/introduction-to-tensorforce/
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plingamp
In the past, i've found that these higher level libraries built on top of TF
are useful for quick model building, but should be used cautiously. By having
default hyperparameters it can be easy to blindly build semi-working models
without knowing what's happening. I would recommend either reading the
associated papers or implementing the models in code (at least once) before
using these pre-built models. That being said, i'm really excited by this
project! I think it'll save researchers a bunch of time.

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naturalgradient
If I understand the project correctly it precisely does not advocate default
hyperparameters but exposes all configurations through the declarative
interface.

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plingamp
I may have used the term hyperparameter too loosely. Yes, this project does a
good job on taking a configuration first approach, but even they set some
defaults. For example, they set relu as their default layer activation
function. I haven't had time to see what other such defaults are being set.

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AlexKuhnle
Thanks for your feedback! To clarify our philosophy regarding default
configurations: On the one hand, we try to make all hyperparameters and
settings of the agents/models centrally configurable, by specifying one
configuration object/file. On the other hand, we try to provide a set of
default values, where it makes sense for the applied user, for whom the full
range of hyperparameters is probably not interesting. In doing so, we try to
combine "the best of both worlds", but sometimes that might lead to conflicts.
This is something we're actively working on, to get the balance right (and
comments are very welcome, best on GitHub).

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cshenton
This is super cool. Might be replacing something I've been building with it.

Are there any benchmarks I could check out? Especially for a3c.

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AlexKuhnle
Hey, glad you like it! We haven't properly benchmarked our models yet, but
it's one of the things at the top of our ToDo list. (However, we will only run
benchmarks on some selected "standard" environments, given our limited
resources.)

