Name
Abstract | ||
|---|---|---|
In this paper we present a multi-agent architecture for trading in electronic markets with asynchronous and related auctions. This architecture enables the development of a multi-agent system for a highly competitive environment, where all participants are competing for a limited number of goods. We define intelligent agent roles that tackle sub problems of trading, and present a solution for combining these results in a distributed environment. The agents' typical tasks are price prediction, bid planning, good allocations, negotiation, among others. We use the Trading Agent Competition (TAC) environment as a case study to illustrate the suitability of our approach. We also present LearnAgents, a multi-agent system based on our architecture that achieved the third place in the 2004 TAC Classic competition. |
Year | Venue | Keywords |
|---|---|---|
2005 | FLAIRS Conference | artificial intelligence,trading systems,software agents,electronic commerce,machine learning.,artificial intelligent,intelligent agent,machine learning,multi agent system,distributed environment,software agent |
Field | DocType | Citations |
Intelligent agent,Autonomous agent,Distributed Computing Environment,Computer science,Common value auction,Artificial intelligence,Distributed computing,Asynchronous communication,Architecture,Simulation,Agent architecture,Machine learning,Negotiation | Conference | 5 |
PageRank | References | Authors |
0.51 | 9 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Alberto R. P. Sardinha | 1 | 10 | 1.94 |
| Ruy Luiz Milidiú | 2 | 192 | 20.18 |
| Patrick M. Paranhos | 3 | 6 | 0.92 |
| Pedro M. Cunha | 4 | 6 | 0.92 |
| Carlos José Pereira De Lucena | 5 | 1027 | 131.61 |