Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
Knowledge transfer is computationally challenging, due in part to the curse of dimensionality, compounded by source and target domains expressed using different features (e.g., do...
The interesting properties of P2P systems (high availability despite peer volatility, support for heterogeneous architectures, high scalability, etc.) make them attractive for dist...
Autonomous robots need the ability to move purposefully and without human intervention in real-world environments that have not been speci cally engineered for them. These environm...
In recent years, large databases of natural images have
become increasingly popular in the evaluation of face and
object recognition algorithms. However, Pinto et al. previously
...