Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
Normative systems in a multiagent system must be able to evolve over time, for example due to actions creating or removing norms in the system. The only formal framework to evalua...
Guido Boella, Gabriella Pigozzi, Leendert van der ...
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
Complex networks exist in a wide array of diverse domains, ranging from biology, sociology, and computer science. These real-world networks, while disparate in nature, often compr...
Haizheng Zhang, C. Lee Giles, Henry C. Foley, John...
We have used semantic technologies to design, implement, and deploy an interdisciplinary virtual observatory. The Virtual Solar-Terrestrial Observatory is a production data framew...
Deborah L. McGuinness, Peter Fox, Luca Cinquini, P...