An Expressive Language and Efficient Execution System for Software Agents

Software agents can be used to automate many of the tedious, time-consuming information processing tasks that humans currently have to complete manually. However, to do so, agent plans must be capable of representing the myriad of actions and control flows required to perform those tasks. In addition, since these tasks can require integrating multiple sources of remote information ? typically, a slow, I/O-bound process ? it is desirable to make execution as efficient as possible. To address both of these needs, we present a flexible software agent plan language and a highly parallel execution system that enable the efficient execution of expressive agent plans. The plan language allows complex tasks to be more easily expressed by providing a variety of operators for flexibly processing the data as well as supporting subplans (for modularity) and recursion (for indeterminate looping). The executor is based on a streaming dataflow model of execution to maximize the amount of operator and data parallelism possible at runtime. We have implemented both the language and executor in a system called THESEUS. Our results from testing THESEUS show that streaming dataflow execution can yield significant speedups over both traditional serial (von Neumann) as well as non-streaming dataflow-style execution that existing software and robot agent execution systems currently support. In addition, we show how plans written in the language we present can represent certain types of subtasks that cannot be accomplished using the languages supported by network query engines. Finally, we demonstrate that the increased expressivity of our plan language does not hamper performance; specifically, we show how data can be integrated from multiple remote sources just as efficiently using our architecture as is possible with a state-of-the-art streaming-dataflow network query engine

MOMIS: Exploiting agents to support information integration

Information overloading introduced by the large amount of data that is spread over the Internet must be faced in an appropriate way. The dynamism and the uncertainty of the Internet, along with the heterogeneity of the sources of information are the two main challenges for today's technologies related to information management. In the area of information integration, this paper proposes an approach based on mobile software agents integrated in the MOMIS (Mediator envirOnment for Multiple Information Sources) infrastructure, which enables semi-automatic information integration to deal with the integration and query of multiple, heterogeneous information sources (relational, object, XML and semi-structured sources). The exploitation of mobile agents in MOMIS can significantly increase the flexibility of the system. In fact, their characteristics of autonomy and adaptability well suit the distributed and open environments, such as the Internet. The aim of this paper is to show the advantages of the introduction in the MOMIS infrastructure of intelligent and mobile software agents for the autonomous management and coordination of integration and query processing over heterogeneous data sources

Active Ontology: An Information Integration Approach for Dynamic Information Sources

In this paper we describe an ontology-based information integration approach that is suitable for highly dynamic distributed information sources, such as those available in Grid systems. The main challenges addressed are: 1) information changes frequently and information requests have to be answered quickly in order to provide up-to-date information; and 2) the most suitable information sources have to be selected from a set of different distributed ones that can provide the information needed. To deal with the first challenge we use an information cache that works with an update-on-demand policy. To deal with the second we add an information source selection step to the usual architecture used for ontology-based information integration. To illustrate our approach, we have developed an information service that aggregates metadata available in hundreds of information services of the EGEE Grid infrastructure

Information brokering on the World Wide Web

Cover title.Includes bibliographical references (p. 6).Stefane Bressan & Thomas Lee