Name
Abstract | ||
|---|---|---|
The effectiveness of an agent architecture is measured by its successful application to real problems. In this paper, we describe an agent architecture, A-Teams, that we have successfully used to develop real-world optimization and decision support applications. In an A-Team, an asynchronous team of agents shares a population of solutions and evolves an optimized set of solutions. Each agent embodies its own algorithm for creating, improving or eliminating a solution. Through sharing of the population of solutions, cooperative behavior between agents emerges and tends to result in better solutions than any one agent could produce. Since agents in an A-Team are autonomous and asynchronous, the architecture is both scalable and robust. In order to make the architecture easier to use and more widely available, we have developed an A-Team class library that provides a foundation for creating A-Team based decision-support systems. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1007/3-540-49057-4_17 | ATAL |
Keywords | Field | DocType |
own algorithm,cooperative behavior,decision support application,agents share,agent architecture,decision-support system,better solution,decision support,asynchronous team,optimized set,a-team class library,decision support system | Space-based architecture,Population,Autonomous agent,Computer science,Decision support system,Software agent,Agent architecture,Systems architecture,Reference architecture,Distributed computing | Conference |
ISBN | Citations | PageRank |
3-540-65713-4 | 32 | 2.79 |
References | Authors | |
10 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| John Rachlin | 1 | 32 | 2.79 |
| Richard Goodwin | 2 | 516 | 40.94 |
| Sesh Murthy | 3 | 119 | 13.28 |
| Rama Akkijaru | 4 | 32 | 2.79 |
| Frederick Wu | 5 | 121 | 12.01 |
| Santhosh Kumaran | 6 | 584 | 66.49 |
| Raja Das | 7 | 32 | 2.79 |