Environment builder for Reinforcement Learning

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elpidiovaldez5

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Environment builder for Reinforcement Learning
« on: May 07, 2019, 02:38:22 am »
I like experimenting with Reinforcement Learning.   Although there are excellent highly sophisticated environments available such as OpenAi gym, I find that I often want to set up a very simple 'toy' grid world problem that presents a very specific learning challenge. 

Does anybody know of an 'Environment Builder' that can be used to rapidly define 2D worlds with simple properties ?

Ideally an Environment Builder would allow:

  • Random (according to some statistical parameters) generation and placement of items in the environment.
  • Labyrinth generation
  • Support movement actions and collision detection
  • Support 1st and 3rd person agent viewpoint
  • Allows actions and responses to be defined for items in the world
  • Can provide a GUI view of the world as the agent moves in the environment
  • Easy integration with RL/Deep Learning environment (tensorflow in my case)
   
I imagine the Environment Builder being a framework, or just a library, in some interactive language (such as python).

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Re: Environment builder for Reinforcement Learning
« Reply #1 on: May 07, 2019, 03:32:28 am »
Blender. The Game Engine inside Blender. Also check out UPBGE - a team is/was worked on a even more upgraded version of Blender's game engine.

I've used Blender quite a lot. It's very easy to use too or maybe I just spent too long in it haha. It's great for rapid testing and all you say, wonderfully easy. However, while BGE/UPBGE is great and perfect in some areas, it isn't top notch as it could be, sorta like a bummy program, but not necessarily bummy either haha. UE4 is a power horse, it can do like, anything, unless I'm wrong. And excellent physics etc omg. Just, UE4 has a learning curve pft! No inuitiveity there.
Emergent          https://openai.com/blog/

 


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