Problem restructuring in negotiation
Management Science
Market-based control: a paradigm for distributed resource allocation
Market-based control: a paradigm for distributed resource allocation
Coalitions among computationally bounded agents
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Computationally Manageable Combinational Auctions
Management Science
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Iterative combinatorial auctions: achieving economic and computational efficiency
Iterative combinatorial auctions: achieving economic and computational efficiency
Selfish Routing and the Price of Anarchy
Selfish Routing and the Price of Anarchy
Combinatorial Auctions
Design, implementation, and evaluation of the linear road bnchmark on the stream processing core
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Algorithmic Game Theory
The complexity of deciding reachability properties of distributed negotiation schemes
Theoretical Computer Science
Multiagent and Grid Systems - Negotiation and Scheduling Mechanisms for Multiagent Systems
Heuristics for negotiation schedules in multi-plan optimization
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Decommitment in multi-resource negotiation
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
CLASP: collaborating, autonomous stream processing systems
Proceedings of the ACM/IFIP/USENIX 2007 International Conference on Middleware
Planning for stream processing systems
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Negotiating socially optimal allocations of resources
Journal of Artificial Intelligence Research
The complexity of contract negotiation
Artificial Intelligence
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We consider a multiagent resource allocation problem where individual users intend to route traffic by requesting the help of entities across a network, and a cost is incurred at each network node that depends on the amount of traffic to be routed. We propose to study contract-based network resource allocation. In our model, users and nodes in the network make contracts before nodes route traffic for the users. The problem is an interesting self-interested negotiation problem because it requires the complete assembly of a set of distinct resources, and there are multiple combinations of distinct resources that could satisfy the goal of negotiation. First, we characterize the network allocation problem and show that finding optimal allocations is NP-complete and is inapproximable. We take both Nash equilibrium and pairwise Nash equilibrium as the solution concepts to characterize the equilibrium allocations. We find that, for any resource allocation game, Nash equilibrium and pairwise Nash equilibrium always exist. In addition, socially optimal allocations are always supported by Nash equilibrium and pairwise Nash equilibrium. We introduce best-response dynamics in which each agent takes a myopic best-response strategy and interacts with each other to dynamically form contracts. We analyze the convergence of the dynamics in some special cases. We also experimentally study the convergence rate of the dynamics and how efficient the evolved allocation is as compared with the optimal allocation in a variety of environments.