Real-time decision support and information gathering system for financial domain

The challenge of the investment domain is that a large amount of diverse information can be potentially relevant to an investment decision, and that, frequently, the decisions have to be made in a timely manner. This presents the potential for better decision support, but poses the challenge of building a decision support agent that gathers information from different sources and incorporates it for timely decision support.These problems motivate us to investigate ways in which the investors can be equipped with a flexible real-time decision support system to be practical in time-critical situations. The flexible real-time decision support system considers a tradeoff between decision quality and computation cost. For this purpose, we propose a system that uses the object oriented Bayesian knowledge base (OOBKB) design to create a decision model at the most suitable level of detail to guide the information gathering activities, and to produce an investment recommendation within a reasonable length of time. The decision models our system uses are implemented as influence diagrams.We validate our system with experiments in a simplified investment domain. The experiments show that our system produces a quality recommendation under different urgency situations. The contribution of our system is that it provides the flexible decision recommendation for an investor under time constraints in a complex environment.