Overcoming Information Overload with Artificial Selective Agents
Authors
Abstract
We describe an approach, based on artificial forms of selective attention, for overcoming the problem of information and interruption overload of intelligent agents. Inspired on natural selective attention studies, we propose a computational model of selective attention that relies on the assumption that uncertain, surprising and motive congruent/incongruent information demands attention from an intelligent agent.
Keywords
Information overload, Selective attention, Emotion; Interest, Value of information, Surprise, Uncertainty, Resource- bounded agents, Personal agents
Related Project
iCIS - Intelligent Computing in the Internet of Services
Conference
13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2014), April 2014