Challenges to Decision Support in a Changing World

Editors:

Marek J. Druzdzel
Decision Systems Laboratory
School of Information Sciences
and Intelligent Systems Program
University of Pittsburgh
e-mail: marek@sis.pitt.edu

Tze Yun Leong
Medical Computing Laboratory
Department of Computer Science
School of Computing
National University of Singapore
Singapore 119260
e-mail: leongty@comp.nus.edu.sg

Abstract:

ONE OF THE MOST DAUNTING CHALLENGES faced by decision support systems is a perpetual change in their environment. Existing decision support methodologies, tools, and frameworks are often difficult to scale up and adapt to changing knowledge, workflow, and operational setting. Systems that have to cope with change need to include methodologies that go outside single theories. For example, systems that are based on probabilistic or decision-theoretic principles will be typically unable to cope with change by themselves, as neither probability theory nor decision theory say much about how decision models are constructed, let alone how they should be modified. The general AI concepts of perception, learning, control, abstraction, and personalization must be inherently designed into the methodological, architectural, and operational aspects of adaptive systems, from application design through software and hardware infrastructure support.