The third task involves implementing the integrated assessment model within the DP solver developed in Task 2. This involves the standard computational issues but also a significant amount of data development, particularly regarding uncertainty and the learning process. Nevertheless, some results have begun to emerge. In fact, we are very pleased with the results we have obtained to date. We are very optimistic that the project is on the right track and that significant results will emerge in the coming year.
Progress is in three areas.
We have successfully converted the PI's stochastic programming integrated assessment model to solution as a dynamic program, using a neural network approach. This work has yet to be documented but we expect to do so over the next few months. Although the approach is considerably slower than conventional solution methods, advantages are that the time horizon is infinite and the structure is considerably more flexible. This is a major breakthrough in that no other integrated assessment models are solved as DP's, primarily because of computational problems. We have also been participating in the Stanford Energy Modeling Forum's study group on uncertainty in integrated assessment models.