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Different samples of SLACER algorithm's outcome. The algorithm follows a link-based incentive approach, that is, nodes make and break links in the network to minimize the effects of others nodes’ selfish behavior. SLACER implements a simple local adaptation rule: Nodes can selfishly increase their own performance (or utility) in a greedy and adaptive way by changing their links and strategy. They do this by copying nodes that appear to be performing better and by making randomized changes with low probability.