OpenAI: Difference between revisions

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==Applications==
==Applications==


===OpenAI GYM===
===OpenAI Gym===
 
[[OpenAI Gym]] is a toolkit for developing and comparing [[reinforcement learning]] (RL) algorithms. While best suited for RL research, it is not restrictive to only that, being able to support alternative methods such as hard coded game solver or other deep learning strategies <ref name="”7”">Brockman et al. (2016). OpenAI Gym. arXiv:1606.01540v1.</ref> <ref name="”8”">Sonawane, B (2018). Getting started with OpenAI Gym. Towards Data Science. https://towardsdatascience.com/getting-started-with-openai-gym-d2ac911f5cbc</ref> <ref name="”9”">OpenAI (2016). OpenAI Gym Beta. OpenAI. https://openai.com/blog/openai-gym-beta/#rl</ref>. The environments are written in Python but, in the future, they'll be easy  to use from any language. OpenAI GYM is compatible with algorithms written in any framework, like [[Tensorflow]] and [[Theano]] <ref name="”9”" />. The platform includes a collection of benchmark problems using a common interface and website where the community can share results and compare the performance of algorithms. Users are also encouraged to share the source code and instructions on how to reproduce their results <ref name="”7”" />.
[[OpenAI GYM]] is a toolkit for developing and comparing [[reinforcement learning]] (RL) algorithms. While best suited for RL research, it is not restrictive to only that, being able to support alternative methods such as hard coded game solver or other deep learning strategies <ref name="”7”">Brockman et al. (2016). OpenAI Gym. arXiv:1606.01540v1.</ref> <ref name="”8”">Sonawane, B (2018). Getting started with OpenAI Gym. Towards Data Science. https://towardsdatascience.com/getting-started-with-openai-gym-d2ac911f5cbc</ref> <ref name="”9”">OpenAI (2016). OpenAI Gym Beta. OpenAI. https://openai.com/blog/openai-gym-beta/#rl</ref>. The environments are written in Python but, in the future, they'll be easy  to use from any language. OpenAI GYM is compatible with algorithms written in any framework, like [[Tensorflow]] and [[Theano]] <ref name="”9”" />. The platform includes a collection of benchmark problems using a common interface and website where the community can share results and compare the performance of algorithms. Users are also encouraged to share the source code and instructions on how to reproduce their results <ref name="”7”" />.


===DALL-E===
===DALL-E===