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open_spiel
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
It's not exactly a tutorial, but OpenSpiel has C++ environments ported to Python that are relatively simple and easy to understand. Procgen would be a more complicated reference to check out as well.
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It's not exactly a tutorial, but OpenSpiel has C++ environments ported to Python that are relatively simple and easy to understand. Procgen would be a more complicated reference to check out as well.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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And I know it's another language, but Julia has made significant strides in their RL packages and are pretty easy to integrate with Python
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If you are more familiar with Python, I highly recommend trying out Numba, before going down the rabit hole of making c++ bindings.
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RustyNEAT
Discontinued Rust implementation of NEAT algorithm (HyperNEAT + ES-HyperNEAT + NoveltySearch + CTRNN + L-systems)
If you want to really speed up your environment several orders of magnitude, you can implement it in cuda/vulkan /opencl. Here is an example of what I did in vulkan https://mobile.twitter.com/MendozaDrosik It allows me to stimulate thousands of agents in parallel. Works wonders especially if you want to use genetic algorithms. If you're interested, I might make python bindings to my minecraft environment. If you write in rust (like I do), then you can add python bindings very easily with PyO3. This is what I did here https://github.com/aleksander-mendoza/RustyNEAT/blob/main/rusty_neat_quick_guide.py (it's GPU accelerated implementation of NEAT algorithm)
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If you want raw speed, parallel execution on GPU or TPU is best. Checkout out our Brax simulator, which uses the XLA compiler and JAX Python frontend: https://github.com/google/brax
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tiny-differentiable-simulator
Tiny Differentiable Simulator is a header-only C++ and CUDA physics library for reinforcement learning and robotics with zero dependencies.
Or our C++ and CUDA Tiny Differentiable Simulator: https://github.com/google-research/tiny-differentiable-simulator
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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