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Latest commit f078711 Dec 18, 2018
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requirements.txt Updated requirements and training script Dec 17, 2018 Updated requirements and training script Dec 17, 2018


Introducing the GoalGridWorld Environment project that was inspired by the grounded language learning (here is the reference paper This project was executed within the OpenAI scholarship program. The GoalGridWorld environment is a matrix where an agent navigates according to commands [go, avoid] to hit or avoid target cells that are represented as randomly displaced pairs of colored objects [triangle, square, circle/red, green, blue]. Basically, there are 18 possible commands but only 8 actual "words". Thanks to an NLP-like approach in this case, an agent can handle more complex/combinatorial commands.

Feel free to use the code to run your experiments.

I want to thank Alec Radford for his mentorship and introducing me to NLP and Joshua Achiam for his valuable advice on reinforcement learning and creating the Spinning Up ( that was extremely helpful for my project.


  • conda install --yes --file requirements.txt
  • Source activate spinningup
  • Python3
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