Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
We study computational problems that arise in the context of iterated dominance in anonymous games, and show that deciding whether a game can be solved by means of iterated weak d...
Given a set of points in a Hilbert space that can be separated from the origin. The slab support vector machine (slab SVM) is an optimization problem that aims at finding a slab (...
Joachim Giesen, Madhusudan Manjunath, Michael Eige...
We consider a problem motivated by the design of ATM (Asynchronous Transfer Mode) networks. Given a physical network and an All-to-All traffic, the problem consists in designing a...
Abstract. How has a stack of n blocks to be arranged in order to maximize its overhang over a table edge while being stable? This question can be seen as an example application for...
Tim Hohm, Matthias Egli, Samuel Gaehwiler, Stefan ...