Stability and Convergence in Selfish Scheduling with Altruistic Agents

Abstract

In this paper we consider altruism, a phenomenon widely observed in nature and practical applications, in the prominent model of selfish load balancing with coordination mechanisms. Our model of altruistic behavior follows recent work by assuming that agent incentives are a trade-off between selfish and social objectives. In particular, we assume agents optimize a linear combination of personal delay of a strategy and the resulting social cost. Our results show that even in very simple cases a variety of standard coordination mechanisms are not robust against altruistic behavior, as pure Nash equilibria are absent or better response dynamics cycle. In contrast, we show that a recently introduced Time-Sharing policy yields a potential game even for partially altruistic agents. In addition, for this policy a Nash equilibrium can be computed in polynomial time. In this way our work provides new insights on the robustness of coordination mechanisms. On a more fundamental level, our results highlight the limitations of stability and convergence when altruistic agents are introduced into games with weighted and lexicographical potential functions.