Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
In many mechanisms (especially online mechanisms), a strategic agent can influence the outcome by creating multiple false identities. We consider voting settings where the mechan...
We present an approach for object recognition that combines detection and segmentation within a efficient hypothesize/test framework. Scanning-window template classifiers are the ...
Abstract. The emergence of complex network structures of relationships between autonomous agents occurs in a wide range of distributed systems. Many researchers have proposed model...
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...