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Peer-to-peer networks are voluntary resource sharing systems among rational agents that are resource providers and consumers. While altruistic resource sharing is necessary for efficient operation, this can only be imposed by incentive mechanisms, otherwise peers tend to behave selfishly. Selfishness in general terms means only consuming resources in order to absorb maximal utility from them and not providing resources to other peers because this would require effort and would not give any utility. In peer-to- peer networks, this behavior, known as free riding, amounts to only downloading content from others and leads to system performance degradation. In this work, we consider a reputation-based mechanism for providing incentives to peers for resource provisioning besides resource consuming. We consider networks where the access technology does not separate upstream and downstream traffic, and these flow through the same capacity-limited access link. Peers do not know other peers' strategies and their intentions to conform to the protocol and share their resources. A separate utility maximization problem is solved by each peer, where the peer allocates a portion of its link bandwidth to its own downloads, acting as client, and it also allocates the remaining bandwidth for serving requests made to it by other peers. The optimization is carried out under a constraint on the level of dissatisfaction the peer intends to cause by not fulfilling others' requests. This parameter is private information for each peer. The reputation of a peer as a server is updated based on the amount of allocated bandwidth compared to the requested one. Reputation acts towards gradually revealing hidden intentions of peers and accordingly guiding the resource allocation by rewarding or penalizing peers in subsequent bandwidth allocations. Our results confirm that the reputation mechanism discourages selfish behavior and drives the system to a state where each peer obtains utility in acco- rdance to its hidden intentions in dissatisfying others.