?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Online+Multi-Robot+Coverage+Path+Planning+in+Dynamic+Environments+Through+Pheromone-Based+Reinforcement+Learning&rft.creator=Champagnie%2C+Kale&rft.creator=Chen%2C+Boli&rft.creator=Arvin%2C+Farshad&rft.creator=Hu%2C+Junyan&rft.description=Two+promising+approaches+to+coverage+path+planning+are+reward-based+and+pheromone-based+methods.+Rewardbased+methods+allow+heuristics+to+be+learned+automatically%2C+often+yielding+a+superior+performance+over+hand-crafted+rules.+On+the+other+hand%2C+pheromone-based+methods+consistently+demonstrate+superior+generalization+and+adaptation+abilities+when+placed+in+unfamiliar+environments.+To+obtain+the+best+of+both+worlds%2C+we+introduce+Greedy+Entropy+Maximization+(GEM)%2C+a+hybrid+approach+that+aims+to+maximize+the+entropy+of+a+pheromone+deposited+by+a+swarm+of+homogeneous+antlike+agents.+We+begin+by+establishing+a+sharp+upper-bound+on+achievable+entropy+and+show+that+this+corresponds+to+optimal+dynamic+coverage+path+planning.+Next%2C+we+demonstrate+that+GEM+closely+approaches+this+upper-bound+despite+depriving+agents+of+basic+necessities+such+as+memory+and+explicit+communication.+Finally%2C+we+show+that+GEM+can+be+executed+asynchronously+in+constant-time%2C+enabling+it+to+scale+arbitrarily.&rft.subject=Computer+aided+software+engineering%2C+Automation%2C+Neural+networks%2C+Reinforcement+learning%2C+Path+planning%2C+Entropy&rft.publisher=Institute+of+Electrical+and+Electronics+Engineers+(IEEE)&rft.date=2024-10-23&rft.type=Proceedings+paper&rft.language=eng&rft.source=+++++In%3A++Proceedings+of+the+2024+IEEE+20th+International+Conference+on+Automation+Science+and+Engineering+(CASE).++(pp.+pp.+1000-1005).++Institute+of+Electrical+and+Electronics+Engineers+(IEEE)%3A+Bari%2C+Italy.+(2024)+++++&rft.format=text&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10193055%2F1%2FKale_GEM.pdf&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10193055%2F&rft.rights=open