1. Intelligent Agents: An Overview From: Chapter 1, A. Canlayan and C. Harrison, Agent: Sourcebook, Wiley 1997.

2. 2 Contents Attributes of intelligent agents End user taxonomy of agents Intelligent agent applications Benefits of agents Business obstacles for agent acceptance Agent use prediction Cost of development

3. 3 Background A definition of an agent: Agent: A person or thing that acts or is capable of acting or is empowered to act for another. The Webster’s New World Dictionary 1970 Two key attributes are pointed out: –An agent does things. –An agent acts on behalf of someone or something.

4. 4 Background Intelligent agent that resides on computers always incorporate these two central attributes. The following definition of an agent will suffice to discuss the business applications of an agent: Software agent: A computing entity that performs user delegated tasks autonomously. Mail filtering agents, information retrieval agents, and desktop automation agents all fit this definition.

5. 5 Attributes of Intelligent Agents The agent possesses the following minimal characteristics: –Delegation –Communication skills –Autonomy –Monitoring –Actuation –Intelligence

6. 6 Attributes of Intelligent Agents The concept of an agent introduces –an indirect management metaphor in a computerized environment –to supplement today‘s mainstream style of direct manipulatioon metaphor via GUI. (Alan, K. (1984). “Computer Software,” Scientific American (March).)

7. 7 Attributes of Intelligent Agents The origins of agent technology are rooted in –the computational intelligence, –software engineering, and –human interface domain.

8. 8 Intelligent Agents Neural Networks KBS Intentional Systems Reasoning Theory Computational Intelligence Software Engineering Human Interface Objects Image and Speech Processing High-level Event Inferencing on-line Monitoring Intelligent Tutoring Interactive Experiments Cognitive Engineering User Modeling

9. 9 Attributes of Intelligent Agents Agent model from a user perspective

10. 10 Agent Task Level Skills Knowledge Communication Skills Task A Priori Knowledge LearningWith User With Other Agents Information Retrieval Information Filtering Coaching Developer Specified User Specified System Specified Dialog Based Memory Based Neural Network Case-Based Neural Expert Interface Speech Social Interagent Communication Language

11. 11 End User Taxonomy of Agents It is helpful to define the agent environment, task and arachitecture. Environment: Agents are designed to performed in a particular environment such as an OS, an application, and a computer network. –Internet agets, OS agents, WWW agents –Assistants, experts, and wizards for a given application

12. 12 End User Taxonomy of Agents Task: Task-specific agents are named accoding to what the agent does. –Information filtering, –informaton retrieval, and –search agents

13. 13 End User Taxonomy of Agents Architecture: Agents are labeled according to the internal knowledge architecture. –Learning agents –Neural agents

14. 14 End User Taxonomy of Agents Taxonomy in this book: –Desktop agents: OS agents: interface agents that provide user assistance with the desktop OS Application agents: interface agents that provide assistance to the user in a particular application Application suite agents: interface agents that help users in dealing with a suite of applications

15. 15 End User Taxonomy of Agents –Internet agents: Web search agents Web server agents: Internet agents that reside at a specific Web site to provide agent services Information filtering agents Information retrieval agents Notification agents Service agents Mobile agents: agents that travel from one place to another to execute user-specified tasks

16. 16 End User Taxonomy of Agents –Intranet agents: Collaborative customization agents: intranet agents that automate workflow processes in business units Process automation agents: intranet agents that atomate business workflow processes Database agents: intranet agents that provide agent services for users of enterprise databases Resource brokering agents: agents that perform resource allocation in client/server architecture

17. 17 Benefits of Agents

18. 18 Benefits of Agents Automation –Particularly applicable for automating: Repetitive behavor of single user Similar behavior of a group of users Repetitive sequential behavior of a number of users in a workflow thread –Repetieive behavior can be time-based or Evenet-based

19. 19 Benefits of Agents Cutomization –Fit into the traditional broadcast and publishing models. –There are three basic architecture choices in the implementation of such a model: the agents can be implemented at the broadcast site, at the user end, or in the middle as a broker agent that serves multiple broadcaster and users.

20. 20 Benefits of Agents Notification: –For instance, such an agent can monitor evetnts of personal changes, and report them to a user.

21. 21 Benefits of Agents Learning: –An agent with a learning capability can learn tasks that can be automated or preference that can be used for customization: Learning and offering to automate the repetitive tasks of a single user, this releiving the user of the need to toil with what, when, and how to automate Leanring the similar attributes of a group of users to customize information based on group characteristics Learning similar behavior of a group of users to provide workgroup productivity enhancement Learning and offering to automate recurrent sequential behavior of a group of users in a workflow thread, thus relieving the workgroup of repetitive tasks

22. 22 Benefits of Agents Tutoring –An agent with a tutoring capability can coach a user in context thanks to its event monitoring and inferencing capabilities, thus reducing the training requirements. –For example, application wizards in the Windows OS

23. 23 Benefits of Agents Messaging –A messaging agent enables user to accomplish tasks off-line at remote sites. –Mobile agents are examples of messaging agents that can transport themselves from place to place to interact with other agents to perfrom tasks on behalf of a user.

24. 24 Business Obstacles for Agent Acceptance Hype –The concept of an intelligent is easily grasped by anyone, and generalized freely. –Users do not care about the complexity in being able to deliver such functionality across all applications. –Unfortunately, the delived functionality cannot easily keep up with the generalized expectations of users. –The solution is to focus on task-specific agents for narrow domains.

25. 25 Business Obstacles for Agent Acceptance User Experience — Indirect Manipulation –A new human-computer interaction beyond today‘s direct manipulation metaphor with GUI –Mass market acceptance of a change in user experience does usually take a number of years. Business Model Security Privacy

26. 26 Agent Use Predictions Software agetns will be accepted as a design paragigm like object-oriented programming or client/server computing according the following observation: –Task-centered computing is slowly replacing the current application centered computing paradigm. –The move toward document-centered computing with OLE and HTML will accelerate this trend. –The software agent model is a better fit to task- centered computing than the current application software model.

27. 27 Agent Use Predictions Prediction for the desktop: –SA will be incorporated into task-specific applications to provide apllication-specific assistance. –SA will supplement today‘s GUIs with intelligent backend services, for example, MS wizards. –This replacement will be very much like the replacement of command line ionterface software with applications supporting industry-standard GUIs.

28. 28 Agent Use Predictions Predication for Intranet –Agents will emerge as critical components of workflow solutions within the enterprise. –Task-specific agents will serve as intelligent front ends to enterprise information systems. –Internet-based agents will get modified for intranet applications to manage the specialized information needs of the corporation.

29. 29 Agent Use Predictions Predication on the Internet –Agents, in the short term, will emerge as information brokers for specialized domains implemented as centralized Web services. –In essence, agents will be components of Web- based services incorporating agent functionality. –Web search engine exemplify such a trend.