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A search and found zero player game using ML-Agent.

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Catch First!

A search and found zero-player game using ML-Agent. I was able to by using ML-Agent package and Code Monkey tutorials, Learn an Agent on a Custom map to catch goals.

Positions of Agent and Goal

agent and goal have four different positions that are randomly chosen for the positions of agent and goal, but each wayPoint position has a radius (0.5) that the position of agent and goal chosen in this radius of random waypoints position.

Neoral Network model

For learning this NN model for the agent I used a basic configuration but learned it on 3.5 million steps and the best mean reward was 0.993
You can see more information in the chart below

Screenshot 2022-12-03 002128

Screenshot 2022-12-03 002608

installation

ml-agents: 0.29.0
ml-agents-envs: 0.28.0
Communicator API: 1.5.0
PyTorch: 1.7.0+cu110
Unity: 2020.3.14

Future

1.I want to turn this into a chatch first game and pit the player against the agent
2.I want to make this agent smarter and increase its routing probability



I would be happy if you have any comments or suggestions for this project

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A search and found zero player game using ML-Agent.

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