Abstract
We study a particular multiagent resource allocation problem with indivisible, but sharable resources. In our model, the utility of an agent for using a bundle of resources is the difference between the value the agent would assign to that bundle in isolation and a congestion cost that depends on the number of agents she has to share each of the resources in her bundle with. The valuation function determining the value and the delay function determining the congestion cost can be agent-dependent. When the agents that share a resource also share control over that resource, then the current users of a resource will require some compensation when a new agent wants to join them using the resource. For this scenario of shared control, we study the existence of distributed negotiation protocols that lead to a social optimum. Depending on constraints on the valuation functions (mainly modularity), on the delay functions (such as convexity), and on the structural complexity of the deals between agents, we prove either the existence of a sequences of deals leading to a social optimum or the convergence of all sequences of deals to such an optimum. We also analyse the length of the path leading to such optimal allocations. For scenarios where the agents using a resource do not have shared control over that resource (i.e., where any agent can use any resource she wants), we study the existence of pure Nash equilibria, i.e., allocations in which no single agent has an incentive to add or drop any of the resources she is currently holding. We provide results for modular valuation functions, we analyse the length of the paths leading to a pure Nash equilibrium, and we relate our findings to results from the literature on congestion games.
Similar content being viewed by others
Notes
To be precise, Sandholm’s work deals with the (mathematically equivalent) problem of task allocation. For a statement in the context of resource allocation and for a full proof, refer to Endriss et al. [14].
swap-deals should not to be confused with the S(wap)-contracts of Sandholm [23], which would correspond to the exchange of two resources between two agents.
Observe that at this point we are using our assumption that delays are symmetric, which entails that if a swap-deal is IR at one level it will also be IR at any other level.
Note that this is different from the swap-deal in which an agent drops a resource and another agent starts using the same resource.
References
Ackermann, H., Röglin, H., & Vöcking, B. (2009). Pure Nash equilibria in player-specific and weighted congestion games. Theoretical Computer Science, 410(17), 1552–1563.
Airiau, S., & Endriss, U. (2010). Multiagent resource allocation with sharable items: Simple protocols and Nash equilibria. In Proceedings of the 9th international joint conference on autonomous agents and multiagent systems (AAMAS-2010) (pp. 167–174).
Bachrach, Y., & Rosenschein, J. S. (2008). Distributed multiagent resource allocation in diminishing marginal return domains. In Proceedings of the 7th international conference on autonomous agents and multiagent systems (AAMAS-2008).
Byde, A., Polukarov, M., & Jennings, N. R. (2009). Games with congestion-averse utilities. Proceedings of the 2nd international symposium on algorithmic game theory (SAGT-2009) (pp. 220–232). Berlin: Springer.
Chevaleyre, Y., Dunne, P. E., Endriss, U., Lang, J., Lemaître, M., Maudet, N., et al. (2006). Issues in multiagent resource allocation. Informatica, 30, 3–31.
Chevaleyre, Y., Endriss, U., Estivie, S., & Maudet, N. (2007). Reaching envy-free states in distributed negotiation settings. In Proceedings of the 20th international joint conference on artificial intelligence (IJCAI-2007).
Chevaleyre, Y., Endriss, U., & Maudet, N. (2010). Simple negotiation schemes for agents with simple preferences: Sufficiency, necessity and maximality. Journal of Autonomous Agents and Multiagent Systems, 20(2), 234–259.
Cramton, P., Shoham, Y., & Steinberg, R. (2006). Combinatorial auctions. Cambridge, MA: MIT Press.
Dunne, P. E. (2005). Extremal behaviour in multiagent contract negotiation. Journal of Artificial Intelligence Research, 23, 41–78.
Dunne, P. E., & Chevaleyre, Y. (2008). The complexity of deciding reachability properties of distributed negotiation schemes. Theoretical Computer Science, 396(1–3), 113–144.
Dunne, P. E., Wooldridge, M., & Laurence, M. (2005). The complexity of contract negotiation. Artificial Intelligence, 164(1–2), 23–46.
Endriss, U., & Maudet, N. (2005). On the communication complexity of multilateral trading: Extended report. Journal of Autonomous Agents and Multiagent Systems, 11(1), 91–107.
Endriss, U., Maudet, N., Sadri, F., & Toni, F. (2003). On optimal outcomes of negotiations over resources. In Proceedings of the 2nd international joint conference on autonomous agents and multiagent systems (AAMAS-2003). New York: ACM Press.
Endriss, U., Maudet, N., Sadri, F., & Toni, F. (2006). Negotiating socially optimal allocations of resources. Journal of Artificial Intelligence Research, 25, 315–348.
Mas-Colell, A., Whinston, M. D., & Green, J. R. (1995). Microeconomic theory. New York: Oxford University Press.
Milchtaich, I. (1996). Congestion games with player-specific payoff functions. Games and Economic Behavior, 13(1), 111–124.
Milchtaich, I. (2004). Social optimality and cooperation in nonatomic congestion games. Journal of Economic Theory, 114(1), 56–87.
Osborne, M. J., & Rubinstein, A. (1994). A course in game theory. Cambridge, MA: MIT Press.
Penn, M., Polukarov, M., & Tennenholtz, M. (2009). Asynchronous congestion games. In M. Lipshteyn, V. Levit, & R. McConnell (Eds.), Graph theory, computational intelligence and thought. Lecture notes in computer science (Vol. 5420, pp. 41–53). Berlin: Springer.
Penn, M., Polukarov, M., & Tennenholtz, M. (2009). Congestion games with load-dependent failures: Identical resources. Games and Economic Behavior, 67(1), 156–173.
Rosenthal, R. W. (1973). A class of games possessing pure-strategy Nash equilibria. International Journal of Game Theory, 2(1), 65–67.
Saha, S., & Sen, S. (2007). An efficient protocol for negotiation over multiple indivisible resources. In Proceedings of the 20th international joint conference on artificial intelligence (IJCAI-2007) (pp. 1494–1499).
Sandholm, T. W. (1998). Contract types for satisficing task allocation: I Theoretical results. In Proceedings of the AAAI spring symposium: Satisficing models.
Shapley, L. S., & Monderer, D. (1996). Potential games. Games and Economic Behaviour, 14(1), 124–143.
Shapley, L. S., & Scarf, H. (1974). On core and indivisibility. Journal of Mathematical Economics, 1(1), 23–37.
Voice, T., Polukarov, M., Byde, A., & Jennings, N. R. (2009). On the impact of strategy and utility structures on congestion-averse games. In Proceedings of the 5th international workshop on Internet and network economics (WINE’09) (pp. 600–607).
Author information
Authors and Affiliations
Corresponding author
Additional information
This is an extended version of a paper presented at the 9th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS-2010) [2].
Rights and permissions
About this article
Cite this article
Airiau, S., Endriss, U. Multiagent resource allocation with sharable items. Auton Agent Multi-Agent Syst 28, 956–985 (2014). https://doi.org/10.1007/s10458-013-9245-x
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10458-013-9245-x