Using Fluorescent in Situ Hybridization (RNA-FISH) to quantify mRNAs in individual Saccharomyces cerevisiae
Arbeitstyp nach Absprache, Masterarbeit, Bachelorarbeit
Recent breakthroughs in Reinforcement Learning (RL) combining classical RL approaches such as Q-Learning or Policy Gradient methods with the Deep Learning paradigm have achieved good performance in many simulated complex singleagent problem domains such as Atari games or Mujoco robotic benchmark tasks. Many problems such as sample inefficiency and transfer to real systems remain, while general solutions for multi-agent systems are still out of reach.
Drone swarms offer many possibilities for applications such as transportation, disaster relief operations, environmental exploration or ad-hoc communication networks. Although the capabilities of individual drones are limited, drone swarms on the other hand promise robust solutions via collaboration. In the limit, this approach requires scalable, robust coordination between the drones not realizable by a single centralized coordinator.