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Chapter 16
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1. | Introduction | |
2. | Historical Account/Background | |
3. | Techniques, Practices, and Applications | |
3.1. | Internet Agents | |
3.2. | Electronic Commerce Agents | |
3.3. | Business Application Agents | |
3.4. | Interface Agents | |
3.5. | Data Mining Agents | |
4. | Supporting Technologies and Research Issues | |
4.1. | Agent Communication Languages | |
4.2. | Mobile Agents | |
4.3. | Autonomous Agents | |
4.4. | Cooperation and Coordination | |
4.5. | Learning | |
5. | Future Trends and Summary | |
References |
An agent is an application that acts on a user's behalf as an intelligent software assistant, simplifying or completely automating a task for the user.
An agent is delegated to perform some task for the user and is given constraints under which it can operate. The agent's processing is attributable to knowledge of the task and the domain in which the task is situated.
Some agent applications use machine learning to improve their performance over time. There are two general types of learning by agents. Some agents adapt to a user's preferences, as given explicitly or implicitly. For example, an agent can learn a user's preference for information on certain topics and then retrieve related items. In this way, the agent becomes customized to a user's preferences over time.
An agent can also learn to perform a given task better. For example, an agent that uses some software tool to perform tasks could learn properties of the tool that would enable it to use the tool more effectively over time. Similarly, an agent that performs in some domain can learn properties of the domain that enable it to perform tasks more effectively over time.
In this chapter, we will describe and discuss the types of agents in use or under research today and the technologies that are being developed to support the use of agents.
The primary types of agents currently deployed include Internet agents, electronic commerce agents, business application agents (including customer service), interface agents, and data mining agents. Intelligent agents to enhance entertainment software are also an active area of advanced development. The supporting technologies for agent applications include knowledge-based systems, machine learning, distributed computing, agent communication languages, and representations of intentional and emotional states.
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