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- W2907172713 abstract "In the last decade, several routing algorithms have been proposed in ad hoc wireless networks. However, most of them require either a high bandwidth, to maintain a full routing table, or suffer a high delay with packet flooding over the network, when the routes are discovered on-demand. As a solution, hybrid approaches, i.e. algorithms that combine on-demand route discovery with proactive updates of the available routes, have shown a good trade-off between low communication overhead and quality of the found routes. One of the approaches used in hybrid algorithms is Multi-Agent Reinforcement Learning (MARL), where the routing problem is addressed as a complex distributed control and learning problem. However, state-of-the-art MARL routing algorithms suffer from some limitations such as either lack of exploration or exploration at the cost of a high communication overhead, slow convergence under network dynamics, or no support for Quality of Service (QoS). In order to overcome such limitations, in this paper, we propose the Q <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sup> -Routing algorithm, which merges existing techniques in wireless routing and enhances them by using techniques from the MARL domain. Simulation results showed that the proposed algorithm is able to outperform well-known ad-hoc routing algorithms in dynamic environments under QoS constraints." @default.
- W2907172713 created "2019-01-11" @default.
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- W2907172713 date "2018-10-01" @default.
- W2907172713 modified "2023-10-17" @default.
- W2907172713 title "Q<sup>2</sup>-Routing : A Qos-aware Q-Routing algorithm for Wireless Ad Hoc Networks" @default.
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- W2907172713 doi "https://doi.org/10.1109/wimob.2018.8589161" @default.
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