Application Of Intelligent Agents Research Articles

New Types of Intelligent Agent Applications

The effective advocacy of human performance modeling research requires scientists to look for opportunities to apply their embryonic technologies in novel areas. We describe three instances where human performance modeling technology is being used to solve problems of high interest to the Air Force.

Special issue: Perspectives on intelligent agents research . . . one year later

A year ago, we published a special issue of The Knowledge Engineering Review entitled Perspectives on Recent Intelligent Agents Research as Viewed through Two Conferences. Our intention was to provide a snapshot of current research on intelligent agents - an area which continues to grow apace - by looking at the work presented at the 1997 instantiations of two of the major events in the Agent calendar. These were the International Conference on Autonomous Agents (Agents '97) and the International Conference and Exhibition on the Practical Application of Intelligent Agents and Multi-Agent Technology (PAAM '97). The result was a group of six papers which together spanned the main areas covered by the conferences as well as identifying some of the challenges faced by the agents community as a whole. In particular, we had summaries by the organisers of both of the conferences, speculation on the future of robotics, surveys of expert assistants and electronic commerce, and a discussion of how agents could be used in workflow management.

Architectures and applications of intelligent agents: A survey

The objective of this paper is twofold. In its first part, we survey the state of the art in research on agent architectures. The architecture of an agent describes its modules and capabilities, and how these operate together. We structure the field by investigating three important research threads, i.e. architectures for reactive agents, deliberative agents and interacting agents. Then we describe various hybrid approaches that reconcile these three threads, aiming at a combination of different features like reactivity, deliberation and the ability to interact with other agents. These approaches are contrasted with architectural issues of recent agent-based work, including software agents, softbots, believable agents, as well as commercial agent-based systems. The second part of the paper addresses software engineers and system designers who are interested in applying agent technology to their problem domains. The objective of this part is to assist these readers in deciding which agent architecture to choose for a specific application. We characterise the most important domains to which the different approaches described in the first part have been applied, propose an application-related taxonomy of agents, and give a set of guidelines to select the right agent (architecture) for a given application.

Multiagent systems: Milestones and new horizons

Research in multiagent systems (MAS), or distributed artificial intelligence (DAI), dates back to the late 1970s. Initial work in the area focused on distributed interpretation of sensor data, organizational structuring and generic negotiation protocols. But several recent developments have helped reshape the focus of the field. Like the rest of Al, the field has matured from being largely exploratory in nature to focusing on formal theories of negotiation, distributed reasoning, multiagent learning and communication languages. The field is also maturing to the point of developing its first few fielded applications. The recent widespread interest in the Internet, the World Wide Web, and intelligent agent applications have further fueled the need for techniques and mechanisms by which agents representing users can interact effectively with other agents in open, dynamic environments. The development of several new international workshops and conferences has helped focus research in the area. The field is poised at a critical juncture, with stimulating problems and challenges promising some very exciting developments in the next few years.

Practical applications of intelligent agents and multiagent technology introduction to the special issue

Practical applications of intelligent agents and multiagent technology introduction to the special issue

Integrating Multiple Reasoning in Intelligent Agent Systems

Intelligent agent systems have the potential for integrating diverse reasoning approaches and emerging computer technologies to solve the complex problems of coordination and control in large distributed systems. The Intelligent Agent Object (IAO) System has been developed to provide a generic fram ework for integrating multiple reasoning and multiple programming paradigms in intelligent agent applications. This development environment currently has forward, backward, or hybrid chaining of production rules, with certainty values, as well as fuzzy logic, available for the intelligent agents created. Additional reasoning approaches are to be subsequently added. Inferencing is carried out without a conventional inference engine through a new technique of message inferencing that dynamically interlinks the four inferencing functions: variable interpretation; rule chaining; execution tracing; object state updating. Both rule-based programming and procedural programming are integrated within a uniform object-oriented structure. Propagation-, access-, and group-oriented programming are also implemented. An intelligent agent-based prototype of an automated guided vehicle operational control system has been developed and tested to demonstrate the capabilities of the IAO development system and further explore the potential for intelligent agent systems.