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 action...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Conference Paper |
| Language: | English |
| Published: |
2017
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. © 2014 IEEE. |
|---|