Efficient Resource Allocation with Non-Concave Objective Functions
Computational Optimization and Applications
Resource Allocation with Wobbly Functions
Computational Optimization and Applications
Resource-Oriented Multicommodity Market Algorithms
Autonomous Agents and Multi-Agent Systems
IEEE Intelligent Systems
Efficient Resource Allocation with Noisy Functions
WAE '01 Proceedings of the 5th International Workshop on Algorithm Engineering
Exchange market for complex commodities: search for optimal matches
Journal of Experimental & Theoretical Artificial Intelligence
Applying the generalized Vickrey auction to pricing reliable multicasts
QofIS'02/ICQT'02 Proceedings of the 3rd international conference on quality of future internet services and internet charging and QoS technologies 2nd international conference on From QoS provisioning to QoS charging
| Hi-index | 0.00 |
General equilibrium theory has been proposed for resource allocation in computational markets. The basic procedure is that agents submit bids and that a resource (re)allocation is performed when a set of prices (one for each commodity) is found such that supply meets demand for each commodity. For successful implementation of large markets based on general equilibrium theory, efficient algorithms for finding the equilibrium are required. We discuss some drawbacks of current algorithms for large scale equilibrium markets and present a novel distributed algorithm, \textsc{CoTree}, which deals with the most important problems. \textsc{CoTree} is communication sparse, fast in adapting to preference changes of a few agents, have minimal requirements on local data, and is easy to implement.