CISUC

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


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