1. Current research in Intelligence Agents Victor Govindaswamy

2. Contents Introduction Example uses of Agents in –World Wide Web –Water systems –Smart Cars –Virtual reality-based training –Medical image processing systems Conclusion

3. Introduction Roles of intelligence agents have expanded since the 1990s… Variety of roles These roles are demonstrated in recent projects such as –Smart Cars, –World Wide Web, –Medical image processing, –Monitoring and analyzing processes, –Virtual reality-based training systems –Water systems.

4. Example use of Agents in World Wide Web Sapp, D.; Shang, Y., Intelligent Web representatives, Proceedings 11th International Conference on Tools with Artificial Intelligence 1999. Introduced a design and implementation of an intelligent agent that is based on existing Internet and Web technologies 3 main design parts to fulfill the need –for a natural language parser, –to represent knowledge and –for effective communication between the user and the computer.

5. Example use of Agents in World Wide Web Sapp, D.; Shang, Y., Intelligent Web representatives, Proceedings 11th International Conference on Tools with Artificial Intelligence 1999. Splits a sentence into its subject, verb and predicate using a parser –3 main parts for the parser’s algorithms: Splits apart the verb by using a database of known verbs Search the unknown subject and predicate for keywords Return the contents of the sentence in a usable format The agent narrows down the user’s question to a few key terms Pattern matched to find the best answer Uses Extensible markup language (XML) –a language was developed based on XML for searching the database and a separate parser to sift through the content and locate the answer. As for communication between user and communication, Microsoft Agent is used – voice recognition and other advanced features.

6. Example use of Agents in Smart Cars Bourbakis, N.; Findler, M., Smart cars as autonomous intelligent agents, Proceedings 13th IEEE International Conference on Tools with Artificial Intelligence, 2001. Propose an idea to use intelligent agents in a smart car to gather information related to its surrounding environment Agents are being used to –determine its position and distance relative to other moving and stationary objects –detect motion and track behavioral patterns of other objects –exchange information via internet with the other moving objects in order to cooperate and negotiate a safe environment during the journey

7. Example use of Agents in water sharing Le Bars, M.; Attonaty, J.M., A multi-agent system to the common management of a renewable resource: application to water sharing, Proceedings 13th IEEE International Conference on Tools with Artificial Intelligence, 2001 Propose that intelligent agents can be used to solve the water sharing problem among farmers in France Current approaches such as linear programming or game theory are based on assumptions that –the people involved are completely rational and include only a limited number of people.. –Not dynamic Building an Agent-Based Modeling (ABM) with a Multi-Agent approach that enables negotiations among a variety and an ever- increasing number of players by taking into consideration –water allocation rules, –the players’ changing attitude and behavior.

8. Example use of Agents in Virtual Reality-based Training Systems Fuhua Lin; Chuan-Jun Su; Tseng, M.M., An agent-based approach to developing intelligent virtual reality-based training systems, Proceedings 11th International Conference on Tools with Artificial Intelligence, 1999. Introduce an agent-based approach to modeling intelligent Virtual Reality-based Training Systems (VRTS) –to help companies train their employees. The characteristics of this approach includes –An agent-based architecture, –Using Petri Nets modeling is also used to realize communication, coordination and task control among agents, and task plan designing, pedagogical knowledge modeling, and behavior modeling of virtual objects. –Several agents are being used for training-task planning, simulation, performance evaluation, instruction and interfacing.

9. Example use of Agents in interpreting medical images Popescu, M.; Yi Shang, An agent-based approach for interpreting medical images, Proceedings 11th International Conference on Tools with Artificial Intelligence, 1999. Use two types of agents in their agent- based approach for interpreting medical images – patient representative and receives an image of the patient from a web-based interface and send it to a radiologist agent –radiologist interprets the image using different image analysis algorithms has a knowledge of anatomy that applies to all imaging modalities and know-how of the specific physics of every modality in order to interpret a given image

10. Conclusion All these projects are trying to make the agents more intelligent than ever. Although the agents’ objectives might be different and specific to a task, humankind are inching their way to the ultimate goal of making agents as intelligent or better yet, more intelligent than humans.