The effective field of view paradigm: adding representation to a reactive system
Dynamic environments pose multiple problems for autonomous agents. Traditionally, agents were designed to develop an internal model of the world and use it to create plans to achieve their goals. Such a strategy fails when the actual environment differs from the stored representation. This realization led to reactive agents, which stored no model of the world. Today, most researchers would agree that representation is not intrinsically bad, but the cost of keeping an arbitrary amount of representation up-to-date in a dynamic environment outweighs its benefits. This paper presents a simple task-dependent representation system, called the effective field of view, which can be used to augment a reactive agent and improve its competence at a variety of tasks. This system has been embodied in two situated autonomous agents. With the first, the amount of representation necessary for its tasks is quantified, as well as the performance gains. With the second, it is shown how the effective field of view can be used in a hierarchical layered agent architecture. This paper shows that the effective field of view can dramatically increase agent performance.
reactive agents task-oriented representation task-oriented perception perception/action systems robotics computer vision markers hierarchical agent architecture deictic representations spatial representation