The rapid advances in wireless communication technology has led to an extraordinary progress in the adhoc type of networking. The mobile adhoc networks being a subtype of the adhoc network almost poses the same characteristics of the adhoc network, presenting multiple challenges in framing a route for the transmission of the information from the source to the destination. So the paper proposes a routing method developed based on the reinforcement learning, exploiting the node information's to establish a route that is short and stable. The proposed method scopes to minimize the energy consumption, transmission delay, and improve the delivery ratio of the packets, enhancing the throughput. The efficiency of the proposed method is determined by validating its performance in the network simulator-II, in terms of the energy consumption, delay in the transmission and the packet delivery ratio.

wireless communication Adhoc networks MANET routing protocols reinforcement learning energy consumption transmission delay and packet delivery ratio