Defining Tasks and Actions Complexity-Levels via Their Deliberation Intensity Measures in the Layered Adjustable Autonomy Model

In Multi-agent Systems (MAS), agents perform a variety of actions to autonomously complete a number of tasks. In this paper, we describe a mechanism to measure a task´s deliberation intensity and apply the mechanism in the Layered Adjustable Autonomy (LAA) model. Basically, the number of actions that the agents need to do to complete a particular task determines the task´s deliberation intensity. Consequently, each of the actions deliberation intensity determines its complexity-level. Actions complexity levels are categorized as high-level if the action is deliberative, intermediate-level if the action pseudo-deliberative and low-level if the action is non-deliberative. Ultimately, the deliberation intensity measure of a task and its actions identify different aspects of the agents´ and the actions´ parameters including the deliberation length and the autonomy configuration of the LAA model.