  This paper presents a solution for reducing the ill effects of free-riders in
decentralised unstructured P2P networks. An autonomous replication scheme is
proposed to improve the availability and enhance system performance. Q-learning
is widely employed in different situations to improve the accuracy in decision
making by each peer. Based on the performance of neighbours of a peer, every
neighbour is awarded different levels of ranks. At the same time a
low-performing node is allowed to improve its rank in different ways.
Simulation results show that Q-learning based free riding control mechanism
effectively limits the services received by free-riders and also encourages the
low-performing neighbours to improve their position. The popular files are
autonomously replicated to nodes possessing required parameters. Due to this
improvement of quantity of popular files, free riders are given opportunity to
lift their position for active participation in the network for sharing files.
Q-feed effectively manages queries from free riders and reduces network traffic
significantly
