In many practical scenarios, nodes gathering at points of interest yield sizable connected components (clusters), which sometimes comprise the majority of nodes. While recent anal...
In the last decade, there has been a massive increase in network research across both the social and physical sciences. In Physics and Mathematics, there have been extensive work o...
The Markov chain approximation method is an effective and widely used approach for computing optimal values and controls for stochastic systems. It was extended to nonlinear (and p...
We consider the problem of computing market equilibria and show three results. (i) For exchange economies satisfying weak gross substitutability we analyze a simple discrete versi...
Bruno Codenotti, Benton McCune, Kasturi R. Varadar...
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...