Abstract
This paper explores the use of a computational procuring clock
auction to induce human agents to approximate the solutions to
discrete constrained optimization problems. Economic and
computational properties of the auction are studied through a
series of laboratory experiments. The experiments are designed
around potental application of the auction as a secondary
institution that approximates the solution to difficult
computational problems that occur within the primary 'smart
market,' and show that the auction is effective and robust in
eliciting and processing suggestions for improved schedules.
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