Intelligent Software Agents Lab at Carnegie Mellon University's
Robotics Institute envisions a world in which autonomous,
intelligent software programs, known as software agents,
undertake many of the operations performed by human users
of the World Wide Web, as well as a multitude of other tasks.
Agents Lab has developed the RETSINA
multi-agent system infrastructure and has applied that infrastructure
and its agents to many domains, including
The RETSINA functional architecture consists of four basic
agents -- interact with users, receive user input,
and display results.
agents -- help users perform tasks, formulate problem-solving
plans and carry out these plans by coordinating and exchanging
information with other software agents.
agents -- provide intelligent access to a heterogeneous
collection of information sources.
agents -- help match agents that request services
with agents that provide services.
research addresses the problem of how to facilitate communication
among agents of different types. We have proposed middle or
matchmaker agents to serve as liasons between agents that
request services and agents that provide services. To increase
interagent communication, we have also developed an agent
capability description language (ACL) that allows otherwise
incompatible agents to communicate.
part of the RETSINA infrastructure of reusable agents, middle
agents represent an important step in our ongoing effort to
provide a foundation that will allow heterogeneous agent types
and architectures to interoperate successfully. Each RETSINA
agent has four reusable modules for communicating, planning,
scheduling, and monitoring the execution of tasks and requests
from other agents.
Communication and Coordination module accepts and
interprets messages and requests from other agents.
Planning module takes as input a set of goals and
produces a plan that satisfies the goals.
Scheduling module uses the task structure created
by the planning module to order the tasks.
Execution module monitors this process and ensures
that actions are carried out in accordance with computational
and other constraints.
is a graphic representation of the RETSINA agent architecture:
website details our research, infrastructure,
applications and publications.
publication detailing our agent infrastructure and multiagent
environment follows. See Publications
page for complete listing.
Sycara, Joseph A. Giampapa, Brent K. Langley, and Massimo
Paolucci "The RETSINA MAS, a Case Study," Software
Engineering for Large-Scale Multi-Agent Systems: Research
Issues and Practical Applications, Alessandro Garcia,
Carlos Lucena, Franco Zambonelli, Andrea Omici, Jaelson
Castro, ed., Springer-Verlag, Berlin Heidelberg, Vol. LNCS
2603, July 2003, pp. 232--250.
Sycara, our Lab leader and Principal Research Scientist, can
be reached at katia at cs dot cmu dot edu.