The application of reinforcement learning algorithms to Partially Observable Stochastic Games (POSG) is challenging since each agent does not have access to the whole state inform...
Alessandro Lazaric, Mario Quaresimale, Marcello Re...
Hard problems for metaheuristic search can be a source of insight for developing better methods. We examine a challenging instance of such a problem that has exactly two local opt...
While in general trading off exploration and exploitation in reinforcement learning is hard, under some formulations relatively simple solutions exist. Optimal decision thresholds ...
In this paper, we study the perturbation operator of Iterated Local Search. To guide more efficiently the search to move towards new promising regions of the search space, we intro...
This paper explores the potential impact of collaborative technologies on improving management education. The first goal is to expose students to tools and practices that not only...