Artificial Intelligence
Tcl and the Tk toolkit
Communications of the ACM
KQML as an agent communication language
CIKM '94 Proceedings of the third international conference on Information and knowledge management
The Stanford Digital Library Project
Communications of the ACM
Communications of the ACM
Social knowledge in multi-agent systems
Mutli-agents systems and applications
Social Knowledge in Multi-agent Systems
EASSS '01 Selected Tutorial Papers from the 9th ECCAI Advanced Course ACAI 2001 and Agent Link's 3rd European Agent Systems Summer School on Multi-Agent Systems and Applications
Organization of social knowledge in multi-agent systems
Integrated Computer-Aided Engineering
Java-based and secure learning agents for information retrieval in distributed systems
Information Sciences: an International Journal
The benefits of using mobile agents in distributed environments
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Applications of agent technology in communications: a review
Computer Communications
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Vast amounts of image data are constantly being collected from a variety of remote sensors deployed on satellites and other platforms. This data has scientific, governmental, and commercial applications in agriculture, forestry, geology, mapping, and crisis management. Specific uses include analyzing crop yield and crop disease; tracking old-growth forest depletion; locating oil and mineral deposits; precisely locating lakes, rivers, roads, and buildings; and assessing earthquake, flood, and hurricane damage.As new commercial satellites with next generation sensors came on-line, satellite data applications will increase dramatically. These new sensors can discriminate objects as small as one square meter, allowing users to discern individual cars on roads and trees in forests.To solve their problems, however, users often need more than raw imagery. A map maker, for instance, might require geographically referenced imagery that is postprocessed to make features such as roads clearly visible. An oil company pipeline monitoring project might require that the pipeline be annotated and the data analyzed to depict urban features and oil leakage. Many applications may need more than one image to cover a particular study area, requiring that the images be registered to a common map and scale and mosaicked to produce a composite image. In short, consumers need information, not data.Unfortunately, the infrastructure that would enable consumers to easily obtain the information they need does not exist today. Currently, just to acquire the raw imagery needed to derive the information they seek, consumers mustdetermine the characteristics of the imagery needed to solve their problem (such as spatial resolution, spectral bands, and acquisition date), identify possible sources for obtaining the desired imagery, search or browse the available imagery from each source, typically via interchanges of paper faxes describing search parameters and archive contents, further evaluate candidate images by such means as low-resolution browse images, andplace an order at each selected vendor.Our Genie system implements a prototype software infrastructure to demonstrate electronic one-stop shopping for the imagery and derived information products sought by various classes of consumers. The key architectural element in this infrastructure is the software agent, a program endowed with goals, beliefs, capabilities, and the ability to interact with other agents to serve the purposes of the individual or organization it represents. The infrastructure consists of collections of different types of agents acting on behalf of different individuals or organizations in the remote-sensing information marketplace.