Agent's autonomy adjustment via situation awareness

Abstract

Interactions between autonomous agents (humans and software) are necessary to increase the system's awareness, support agents' decision-making abilities and subsequently reduce the risks of failure. The challenge, however, is to formulate a mechanism that specifies when an agent or a human should take the initiative to interact. In this paper, we propose a Situation Awareness Assessment (SAA) model of autonomy adjustment with situation awareness capabilities in a decentralized environment. The SAA model systematizes the interactions to assist agents' decision-making and improve the systems' performance. The model inspects if an agent has the required awareness of a situation to be satisfactorily autonomous, otherwise, it intervenes the agent with feedback about the situation. An example scenario demonstrates the SAA ability to facilitate improved autonomous behavior in agents. © 2014 Springer International Publishing Switzerland.