Computational Requirements of Statistical Learning: Ideal Decision-Making for More Sustainable Urban Environments

Investigators
  Victoria C.P. Chen (PI)
  Michael E. Chang
  Ellis Johnson
  Eva K. Lee
  Bruce Beck

Sponsor
  US EPA

Project Website
  None

Period of Performance
  Start: 5/15/00
  End: 6/20/03
Last Updated: 09/06/02
    Project Description
The objective of this research is to develop a tool that can be used to extract more relevant information from existing environmental deterministic and stochastic models than would otherwise be possible using current approaches. Decision-makers use models to examine systems and to predict system responses to prescribed stimulants. The products of this research therefore, are directly aimed at the users and developers of environmental models. Those who develop deterministic and stochastic models may use the decision-making framework developed in this research to guide them in building an interface between their models and the user. Such an interface will enable the users to utilize the models more efficiently and effectively when the models are used to explore how a system responds to a potential action or set of actions. It is expected that the users desire to select the optimum course of action either to maximize expected benefits or to minimize expected costs while maintaining other state conditions.