Abstract
Many routing algorithms were proposed in wireless ad hoc networks. The main disadvantage of those algorithms is, we need to have reliable knowledge about the network, and also expected average per packet reward criterion is also high. In this paper, the authors have discussed about d-AdaptOR algorithm which doesn't need reliable knowledge about the network structure and channel statistics. This scheme reduces the average per packet reward criterion. This scheme is also advantageous than the classical routing algorithms when we want to broadcast a packet. In this scheme, the next relay node depending upon Estimated Best Score (EBS) has been selected. This algorithm explores and exploits the opportunities in the network. This scheme jointly tackles the problem of learning and routing in an opportunistic context, where the network model is characterized by the transmission success probabilities.
Keywords
Routing, Adaptive, EBS, Reinforcement Learning, Opportunistic

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