Paper Info
Title
Discovering And Composing Distributed Atomic Agents For Imagery And Geospatial Problem Solving
Abstract
This paper describes our approach to building a scalable, flexible agent-based architecture for imagery and geospatial processing. Central to this approach is the agent discovery and composition mechanism which scales to support networks with thousands of agents. The agent architecture implements over 100 imagery and geospatial processing agents based on the Java Advanced Imaging and OpenMap(TM) APIs. The agents are distributed over a Jini enabled network, and communicate with one another via JavaSpaces. We discuss our "atomic" approach in this paper: developing low-level processing agents that are used by application of specific agents. We discuss several concepts in this approach: agent lookup and discovery through traditional information retrieval techniques, the ability to rapidly prototype agents based on commercial software products, and a knowledge management approach that reuses prior processing approaches and results. We present results demonstrating the scalability of our agent discovery and composition mechanism to compare them with other traditional discovery mechanisms, and demonstrate how the discovery mechanism scales to support thousands of agents.
Year
DOI
Venue
2002
10.1142/S021800140200212X
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
multi-agent systems, agent discovery, agent composition, image processing, geographic information systems
Geographic information system,Computer science,Commercial software,Multi-agent system,Artificial intelligence,Distributed computing,Geospatial analysis,World Wide Web,Software agent,Agent architecture,Java,Machine learning,Scalability
Journal
Volume
Issue
ISSN
16
8
0218-0014
Citations 
PageRank 
References 
1
0.38
6
Authors
3
Name
Order
Citations
PageRank
James J. Nolan172.03
Arun K. Sood26510.81
Robert Simon310.38