Abstract
We consider network contribution games, where each agent in a social network has a budget of effort that he can contribute to different collaborative projects. Depending on the contribution of the involved agents a project will be successful to a different degree, and to measure the success we use a reward function for each project. Every agent is trying to maximize the reward from all projects that it is involved in. We consider pairwise equilibria of this game and characterize the existence, computational complexity, and quality of equilibrium based on the types of reward functions involved. For example, when all reward functions are concave, we prove that the price of anarchy is at most 2. For convex functions the same only holds under some special but very natural conditions. A special focus of the paper are minimum effort games, where the success of a project depends only on the minimum effort of any of the participants. Finally, we briefly discuss additional aspects like approximate equilibria and convergence of dynamics.
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