A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Successful approaches to the robot localization problem include Monte Carlo particle ļ¬lters, which estimate non-parametric localization belief distributions. However, particle ļ...
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponentās action frequencies and building an opp...
k- and t-optimality algorithms [9, 6] provide solutions to DCOPs that are optimal in regions characterized by its size and distance respectively. Moreover, they provide quality gu...
Recent applications of game theory in security domains use algorithms to solve a Stackelberg model, in which one player (the leader) ļ¬rst commits to a mixed strategy and then th...