The most sophisticated technology in common use today is an automatic setback thermostat.
Tremendous potential remains for conserving gas and electricity resources.
We thus consider the design of environmental control strategies as an optimization problem in which the goal is to minimize energy usage and maximize the comfort of the residents. We have constructed a prototype adaptive control system in an actual residence using neural network reinforcement learning and prediction techniques. By predicting lifestyle patterns of the residents, the system can infer rules of operation that anticipate inhabitant needs while conserving energy. I will describe our experiences and results in the first three years of the project. Speaker Information Mike Mozer is Associate Professor in the Department of Computer Science and Institute of Cognitive Science Science at University of Colorado, Boulder.