Artificial decision making under uncertainty in intelligent buildings
Abstract
Our hypothesis is that by equipping certain agents in a multi-agent
system controlling an intelligent building with automated decision
support, two important factors will be increased. The first is energy
saving in the building. The second is customer value—how the
people in the building experience the effects of the actions of the
agents. We give evidence for the truth of this hypothesis through
experimental findings related to tools for artificial decision making.
A number of assumptions related to agent control, through monitoring
and delegation of tasks to other kinds of agents, of rooms at a test
site are relaxed. Each assumption controls at least one uncertainty
that complicates considerably the procedures for selecting actions
part of each such agent. We show that in realistic decision
situations, room-controlling agents can make bounded rational
decisions even under dynamic real-time constraints. This result can
be, and has been, generalized to other domains with even harsher time
constraints.
Sample citation
Magnus Boman,
Paul Davidsson, and
Håkan L. S. Younes. 1999.
Artificial decision making under uncertainty in intelligent buildings. In
Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, edited by Kathryn B. Laskey and Henri Prade, 65–70, Stockholm, Sweden. Morgan Kaufmann Publishers.
Full paper (6 pages, 19 references)