About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
ICAC 2005
Conference paper
How can we trust an autonomic system to make the best decision?
Abstract
Autonomic Computing has gained widespread attention over the last few years for its vision of developing applications with autonomie or self-managing behaviors [1]. New approaches to the design and implementation of autonomie systems have emerged, including the use of goal policies[2], utility functions [2], intelligent monitoring, data mining, reinforcement learning, and planning. Unfortunately, these new approaches do nothing to reduce administrators' skepticism towards automation - how is an administrator to believe that an autonomie system will help his systems perform better? In this report, we describe an approach by which an autonomie system can win the trust of its users, and can continuously adjust itself to make better decisions based on the users' preferences.