Abstract
In resource allocation games, selfish players share resources that are needed in order to fulfill their objectives. The cost of using a resource depends on the load on it. In the traditional setting, the players make their choices concurrently and in one-shot. That is, a strategy for a player is a subset of the resources. We introduce and study dynamic resource allocation games. In this setting, the game proceeds in phases. In each phase each player chooses one resource. A scheduler dictates the order in which the players proceed in a phase, possibly scheduling several players to proceed concurrently. The game ends when each player has collected a set of resources that fulfills his objective. The cost for each player then depends on this set as well as on the load on the resources in it – we consider both congestion and cost-sharing games. We argue that the dynamic setting is the suitable setting for many applications in practice. We study the stability of dynamic resource allocation games, where the appropriate notion of stability is that of subgame perfect equilibrium, study the inefficiency incurred due to selfish behavior, and also study problems that are particular to the dynamic setting, like constraints on the order in which resources can be chosen or the problem of finding a scheduler that achieves stability.
This research was supported in part by the European Research Council (ERC) under grants 267989 (QUAREM) and 278410 (QUALITY), and by the Austrian Science Fund (FWF) under grants S11402-N23 (RiSE) and Z211-N23 (Wittgenstein Award).
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- 1.
In this example we require the players to choose their paths incrementally, which is not the general definition we use in the paper.
- 2.
We use “objectives” rather than “strategies” as the second will later be used for dynamic games.
- 3.
It is interesting to allow players to use “redundant resources”; a player’s choice of resources should contain one of his objectives. While in the traditional setting, using a redundant resource cannot be beneficial, in the dynamic setting, it is, as a variant of Example 1 demonstrates.
- 4.
Throughout this paper, we consider pure strategies as is the case in the vast literature on RAGs.
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Avni, G., Henzinger, T.A., Kupferman, O. (2016). Dynamic Resource Allocation Games. In: Gairing, M., Savani, R. (eds) Algorithmic Game Theory. SAGT 2016. Lecture Notes in Computer Science(), vol 9928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-53354-3_13
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