k-order additive discrete fuzzy measures and their representation
Fuzzy Sets and Systems - Special issue on fuzzy measures and integrals
Computationally Manageable Combinational Auctions
Management Science
Flexible double auctions for electionic commerce: theory and implementation
Decision Support Systems - Special issue on economics of electronic commerce
Utilities as Random Variables: Density Estimation and Structure Discovery
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
On the Communication Complexity of Multilateral Trading: Extended Report
Autonomous Agents and Multi-Agent Systems
Combinatorial Auctions
The complexity of contract negotiation
Artificial Intelligence
Modeling complex multi-issue negotiations using utility graphs
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Negotiating over small bundles of resources
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Introduction: special issue on distributed constraint satisfaction
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Combinatorial auctions with k-wise dependent valuations
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Negotiating socially optimal allocations of resources
Journal of Artificial Intelligence Research
Investigating adaptive, confidence-based strategic negotiations in complex multiagent environments
Web Intelligence and Agent Systems
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Multiagent resource allocation is a timely and exciting area of research at the interface of Computer Science and Economics. One of the main challenges in this area is the high complexity of negotiation. In particular, the complexity of the task of identifying rational deals, i.e. deals that are beneficial for all participants, often hinders the successful transfer of theoretical results to practical applications. To address this issue, we propose several protocols designed to tame the complexity of negotiation by exploiting structural properties of the utility functions used by agents to model their preferences over alternative bundles of resources. In particular, we consider domains where utility functions are k-additive (that is, synergies between different resources are restricted to bundles of at most k items) and tree-structured in the sense that the bundles for which there are synergies do not overlap. We show how protocols exploiting these properties can allow for drastically simplified negotiation processes.