Rules of encounter: designing conventions for automated negotiation among computers
Rules of encounter: designing conventions for automated negotiation among computers
Market-based control: a paradigm for distributed resource allocation
Market-based control: a paradigm for distributed resource allocation
Computational Markets to Regulate Mobile-Agent Systems
Autonomous Agents and Multi-Agent Systems
On the Communication Complexity of Multilateral Trading: Extended Report
Autonomous Agents and Multi-Agent Systems
Negotiating socially optimal allocations of resources
Journal of Artificial Intelligence Research
Equilibria, prudent Compromises,and the "Waiting" game
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A new game theoretical resource allocation algorithm for cloud computing
GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
Future Generation Computer Systems
Reliable resources brokering scheme in wireless grids based on non-cooperative bargaining game
Journal of Network and Computer Applications
Tutorial: Resource Management in Cloud Computing
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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Although there are some research efforts toward resource allocation in multi-agent systems (MAS), most of these work assume that each agent has complete information about other agents. This research investigates interactions among selfish, rational, and autonomous agents in resource allocation, each with incomplete information about other entities, and each seeking to maximize its expected utility. This paper presents a proportional resource allocation mechanism and gives a game theoretical analysis of the optimal strategies and the analysis shows the existence of equilibrium in the incomplete information setting. By augmenting the resource allocation mechanism with a deal optimization mechanism, trading agents can be programmed to optimize resource allocation results by updating beliefs and resubmitting bids. Experimental results showed that by having a deal optimization stage, the resource allocation mechanism produced generally optimistic outcomes (close to market equilibrium).