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Reinforcement-Learning-Swarm-Robotics

This is a collaborative project between Michael Mu, Romika Sairam, and Sachin George.

This project is an implementation of reinforcement learning to the field of swarm robotics. This means we wish to introduce a massive number of agents with only the simple ability of moving to work together to accomplish more complex tasks.

Currently, the goals of the project are as follows:

  1. Collaboratively search for a target.
  2. Collaboratively move a target that is too large for an individual agent to move.
  3. Coordinate to move the target to a destination.

Glossary:

Some terms we use are self-defined to increase simplicity of language. Their explicit meanings are listed here.

Target - A part of the environment which we wish to use our agents to find and move. In our default environment, this is a ragdoll humanoid.

Destination - A location in the environment which we wish the target be brought to.

The real-world equivalent of this environment would be an unconscious individual that we bring to a safe location or something similar.

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Massive Multi-Agent Problem for Reinforcement Learning

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