Recent years have seen extensive investigation of the information aggregation properties of prediction markets. However, relatively little is known about conditions under which a ...
Krishnamurthy Iyer, Ramesh Johari, Ciamac Cyrus Mo...
Abstract. The problem of averaging outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The fuz...
Abstract— This paper proposes a novel two-stage optimization method for robust Model Predictive Control (RMPC) with Gaussian disturbance and state estimation error. Since the dis...
The majority of the work in the area of Markov decision processes has focused on expected values of rewards in the objective function and expected costs in the constraints. Althou...
We consider an optimization problem in probabilistic inference: Given n hypotheses Hj, m possible observations Ok, their conditional probabilities pk j, and a particular Ok, selec...