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Found 5 papers, 1 papers with code
Decentralized Multi-Agent Reinforcement Learning with Global State Prediction
We provide a comprehensive study over four well-known deep reinforcement learning algorithms in environments with obstacles, measuring performance as the successful transport of the object to the goal within a desired time-frame.
Flow-FL: Data-Driven Federated Learning for Spatio-Temporal Predictions in Multi-Robot Systems
In both variants, we use a data-driven mechanism to synchronize the learning process in which robots contribute model updates when they collect sufficient data.
SMAC: Symbiotic Multi-Agent Construction
We present a novel concept of a heterogeneous, distributed platform for autonomous 3D construction.
A Minimalistic Approach to Segregation in Robot Swarms
We present a decentralized algorithm to achieve segregation into an arbitrary number of groups with swarms of autonomous robots.
Robotics
Decentralized Connectivity-Preserving Deployment of Large-Scale Robot Swarms
We present a decentralized and scalable approach for deployment of a robot swarm.
Robotics Multiagent Systems
