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Our hypothesis is that by equipping certain agents in a multi-agent systemcontrolling an intelligent building with automated decision support, twoimportant factors will be increased. The first is energy saving in thebuilding. The second is customer value---how the people in the buildingexperience the effects of the actions of the agents. We give evidence for thetruth of this hypothesis through experimental findings related to tools forartificial decision making. A number of assumptions related to agent control,through monitoring and delegation of tasks to other kinds of agents, of roomsat a test site are relaxed. Each assumption controls at least one uncertaintythat complicates considerably the procedures for selecting actions part of eachsuch agent. We show that in realistic decision situations, room-controllingagents can make bounded rational decisions even under dynamic real-timeconstraints. This result can be, and has been, generalized to other domainswith even harsher time constraints.

Artificial Decision Making Under Uncertainty in Intelligent Buildings