— Modeling robot motion planning with uncertainty in a Bayesian framework leads to a computationally intractable stochastic control problem. We seek hypotheses that can justify a...
Andrea Censi, Daniele Calisi, Alessandro De Luca, ...
Motivated by online ad allocation, we study the problem of simultaneous approximations for the adversarial and stochastic online budgeted allocation problem. This problem consists...
Vahab S. Mirrokni, Shayan Oveis Gharan, Morteza Za...
In this paper, we show that tracking multiple people whose paths may intersect can be formulated as a convex global optimization problem. Our proposed framework is designed to exp...
Horesh Ben Shitrit, Jerome Berclaz, Francois Fleur...
Time considerations have been largely ignored in the study of vehicle routing problems with stochastic demands, even though they are crucial in practice. We show that tour duratio...
Alan L. Erera, Juan C. Morales, Martin W. P. Savel...
We address a class of problems where decisions have to be optimized over a time horizon given that the future is uncertain and that the optimization decisions influence the time o...