| Abstract |
An effective Decision Support System (DSS) should help its users
improve decision-making in complex, information-rich, dynamic
environments. We present a feature gap analysis of current decision
support technologies, and we identify a set of DSS Desiderata,
properties that can contribute both effectiveness and flexibility to
users in such environments. We show that there is a gap between the
features provided by current DSS technologies and the DSS Desiderata
we aim for. We present a vision of a new approach to building
decision support systems that we call ``evaluator service
networks.'' This approach will enable users to compose decision
behaviors from separate, configurable components, and allows dynamic
construction of analysis and modeling tools from small,
single-purpose evaluator services. The result is a network that can
easily be configured to test hypotheses and analyze the impact of
various choices for elements of decision processes. We have
implemented and tested this design in an interactive version of the
MinneTAC trading agent, an agent designed for the Trading Agent
Competition for Supply Chain Management. We present an example of
an evaluator service network that determines sales prices in a rich,
dynamic trading environment. Additionally we describe visual
interface elements that allow users to see and manipulate the
configuration of the network, and to construct economic dashboards
that can display the current and historical state of any node in the
network. |