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# System prepended metadata

title: 'ERC Projrect: Environment Optimization'

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# ERC Projrect: Environment Optimization


Recommend reading list from QLi:

Application of GNN in control in continous domain 
1. Ekaterina Tolstaya, Fernando Gama, James Paulos, George Pappas, Vijay Kumar, Alejandro Ribeiro Proceedings of the Conference on Robot Learning, PMLR 100:671-682, 2020.`[1](https://proceedings.mlr.press/v100/tolstaya20a.html)

2. Khan, Arbaaz, Ekaterina Tolstaya, Alejandro Ribeiro, and Vijay Kumar. "Graph policy gradients for large scale robot control." In Conference on robot learning, pp. 823-834. PMLR, 2020. [2](http://proceedings.mlr.press/v100/khan20a/khan20a.pdf)


Potention Simulator:
1. Project Malmo [3](https://www.microsoft.com/en-us/research/project/project-malmo/)

2. VectorizedMultiAgentSimulator (VMAS) [4] (https://github.com/proroklab/VectorizedMultiAgentSimulator)

3. AlphaStar [5](https://github.com/deepmind/alphastar)

4. Star craft [6](https://github.com/oxwhirl/smac)


Researcher working in CBF from Mit, Chuchu Fan[7](https://chuchu.mit.edu/)
