Convergence of Peer-to-Peer Collision Avoidance among Unmanned Aerial Vehicles

Abstract

This paper proposes a mechanism of noise tolerance for reinforcement learning algorithms. An adaptive agent that employs reinforcement learning algorithms may receive and accumulate many rewards for its actions. However, the amount of rewards received by the agent is not a guarantee of convergence to an optimal policy of action due to the noises produced by… (More)
DOI: 10.1109/IAT.2007.75

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@article{Volf2007ConvergenceOP, title={Convergence of Peer-to-Peer Collision Avoidance among Unmanned Aerial Vehicles}, author={Premysl Volf and David Sisl{\'a}k and Michal Pechoucek and Magdalena Prokopov{\'a}}, journal={2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'07)}, year={2007}, pages={377-383} }