![Loop to Learn](https://img.itch.zone/aW1nLzQzNTExMDcuZ2lm/original/PDZrfj.gif)
Loop to Learn
A Game of Reinforcement Learning
You are an engineer tasked with optimizing artificial intelligent agents in the completion of spatial navigation tasks to satellites. You have control over the time scale, which aspects of the environment triggers rewards in the agents, and when you want to select the best agent for testing (this is how you clear a level)--
The inputs the agent has available are 10 sensors that enables it to calculate distances of objects in front of it. The agent's output is to rotate and/or move forward. The performance (or fitness) of the best performing agent can be seen in the bottom right corner and is modulated by which factors rewards the agents in their actions.
For example, rewarding agents for the distance to the target means that the shorter the agents' distance is to the satellite at the end of the learning loop, the better its performance is. So be sure to decide how to reward the AIs or they might not even understand the task!
Every time 15 in-game seconds (can be scaled by you) go by, the agents are reset and the bottom half performing agents get updated neural networks through a mutation algorithm.
Status | In development |
Platforms | Windows, HTML5 |
Author | Esben Kran |
Comments
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webgl version seems to do one run and then nothing? [edit: same in dl version]
Thanks for pointing it out! I haven't had time to update it since the original game release but it works in the editor - I believe it's some problems regarding the neural networks :))