Searched for: subject%3A%22Reinforcement%255C+Leaning%255C+%255C%2528RL%255C%2529%22
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Sun, D. (author)
This thesis focuses on management and control of traffic networks, including urban networks and freeway networks, in which we aim to reduce traffic congestion by minimizing the total time spent of all the vehicles in the network, and also consider green mobility by minimizing the total emissions produced by the vehicles. In this thesis, we have...
doctoral thesis 2023
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Yang, Q. (author)
In traditional reinforcement learning (RL) problems, agents can explore environments to learn optimal policies through trials and errors that are sometimes unsafe. However, unsafe interactions with environments are unacceptable in many safety-critical problems, for instance in robot navigation tasks. Even though RL agents can be trained in...
doctoral thesis 2023
document
Jarne Ornia, D. (author)
Besides facing the same challenges as single-agent systems, the distributed nature of complex multi-agent systems sparks many questions and problems revolving around the constraints imposed by communication. The idea that multi-agent systems require communication to access information, to coordinate or simply to sense the environment they are...
doctoral thesis 2023
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Ribeiro, M.J. (author), Ellerbroek, Joost (author), Hoekstra, J.M. (author)
The use of drones for applications such as package delivery, in an urban setting, would result in traffic densities that are orders of magnitude higher than any observed in manned aviation. Current geometric resolution models have proven to be very efficient at relatively moderate densities. However, at higher densities, performance is hindered...
conference paper 2020
Searched for: subject%3A%22Reinforcement%255C+Leaning%255C+%255C%2528RL%255C%2529%22
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