Modeling Workplace Evacuation Behaviors Using Intelligent Agents

Abstract

A major challenge in artificial intelligence has been the development of autonomous agents (AAs) capable of displaying believable behaviors. To achieve such objective, the underlying architectures of these intelligent systems have been designed to incorporate Learning Classifier System that provides an adaptation naturally with the environment. It is expected that through the interaction of this type of components, AAs can implement more intelligent and believable behavior. Although the literature reports several computational models of behaviors, attention, and emotions developed to be included in cognitive agent architectures, these have been implemented as separated processes, disregarding essential interactions between these behaviors whose modeling and computational implementation may increase the believability of actions developed by AAs. In this paper, we propose an evolutive computational model. This model is designed to provide AAs with adequate mechanisms to attend and react to conditions and changes in the environment.