Agents that Reduce Work and Information Overload and Beyond Intelligent Interfaces. Presented by Maulik Oza Department of Information and Computer Science University of California, Irvine [email protected] ICS 205 – Spring 2002. Agents that Reduce Work and Information Overload. Pattie Maes.
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Agents that Reduce Work and Information OverloadandBeyond Intelligent Interfaces
Department of Information and Computer Science
University of California, Irvine
ICS 205 – Spring 2002
Agents that Reduce Work and Information Overload
Figure: The interface agent does not act as an interface or layer between the user and the application. Rather, it behaves as a personal assistant which cooperates with the user on the task. The user is able to bypass the agent.
Figure: The interface agent learns in four different ways: (1) it observes and imitates the user's behavior, (2) it adapts based on user feedback, (3) it can be trained by the user on the basis of examples, and (4) it can ask for advice from other agents assisting other users.
Figure: Simple caricatures convey the state of the agent to the user. The agent can be "alert" (tracking the user's actions), "thinking" (computing a suggestion), "offering a suggestion" (confidence insuggestion is above "tell-me" threshold), "surprised" if the suggestion is not accepted, "gratified" if the suggestion is accepted, "unsure" about what to do in the current situation (confidence below "tell-me" threshold, and thus suggestion is not offered), "confused" about what the user ends up doing, "pleased" that the suggestion it was not sure about turned out to be the right one after all, and "working" or performing an automated task (confidence in prediction above "do-it" threshold).
Beyond Intelligent Interfaces: Exploring, Analyzing, and Creating Success Models of Cooperative Problem Solving