The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...
We investigate network management information for light-path assessment to dynamically set up end-to-end lightpaths across administrative domains. Our focus is on invetigating what...
Recent work on information integration has yielded novel and efficient solutions for gathering data from the World Wide Web. However, there has been little attention given to the ...
Greg Barish, Dan DiPasquo, Craig A. Knoblock, Stev...
Mechanism design is the study of preference aggregation protocols that work well in the face of self-interested agents. We present the first general-purpose techniques for automa...
Tuomas Sandholm, Vincent Conitzer, Craig Boutilier
We present a novel approach to speech processing based on the principle of pattern discovery. Our work represents a departure from traditional models of speech recognition, where t...