Search

Because of the environments in which they will operate, future autonomous systems must be capable of reconfiguring quickly and safely following faults or environmental changes. Past research has shown how, by considering autonomous systems to perform phased missions, reliability analysis can support decision making by allowing comparison of the probability of success of different missions following reconfiguration. Binary decision diagrams (BDDs) offer fast, accurate reliability analysis that could contribute to real-time decision making. However, phased mission analysis using existing BDD models is too slow to contribute to the instant decisions needed in time-critical situations. This paper investigates 2 aspects of BDD models that affect analysis speed: variable ordering and quantification efficiency. Variable ordering affects BDD size, which directly affects analysis speed. Here, a new ordering scheme is proposed for use in the context of a decision-making process. Variables are ordered before a mission, and reordering is unnecessary no matter how the mission configuration changes. Three BDD models are proposed to address the efficiency and accuracy of existing models. The advantages of the developed ordering scheme and BDD models are demonstrated in the context of their application within a reliability analysis methodology used to support decision making in an unmanned aerial vehicle. [ABSTRACT FROM AUTHOR]

This paper presents the development of an integrated system, namely the COMAND-DSS (Decision Support System created under project COMAND), for crisis management and real-time decision support in shipboard flooding emergencies. It employs the case-based reasoning approach to provide swift and effective decision-making support for shipboard personnel during an emergency on ship. The developed system, which focuses on decision support for flooding control, is also thought to be useful as a crew training system. In order to deal with a flooding damage in the COMAND-DSS, a multiple attribute decision-making methodology—Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)—is used to be able to choose the set of counter-flooding tanks that should be filled in order to achieve an optimal response to a flooding accident. The COMAND-DSS is composed of a knowledge base, a reasoning process and a graphical user interface for the shipboard personnel to interact with the system. The friendly windows-based user interface of the COMAND-DSS enables the user to take full advantage of the capabilities of the system in order to make quick decisions. Using this system, when a crisis occurs the optimal decisions and responses can be made in a short time, thereby reducing the risk to life, property and environment. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Automated decision-making systems have been deployed in many industrial, commercial, and financial applications. The needs for such systems are usually motivated by requirements for variation reduction, capacity increase, cost and cycle time reduction, and end-to-end traceability of the transaction or product. Before we can use any automated decision-making system in a production environment we must develop a strategy to insure high quality throughout its entire lifecycle. We need to guarantee its performance through a rigorous Design for Six Sigma process (DFSS). This process includes validation, tuning, and production testing of the system. Once the system is in production we must monitor and maintain its performance over its lifecycle. In this paper we will outline the Six Sigma process that led to the deployment of an automated decision-making system in one of the General Electric Financial Assurance businesses. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]