We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
The performance of IP networks depends on a wide variety of dynamic conditions. Traffic shifts, equipment failures, planned maintenance, and topology changes in other parts of th...
Recent years are seeing an increasing need for on-line monitoring of deployed distributed teams of cooperating agents, e.g., for visualization, or performance tracking. However, i...
This paper presents a knowledge approach to designing team training systems using intelligent agents. We envision a computer-based training system in which teams are trained by pu...
Jianwen Yin, Michael S. Miller, Thomas R. Ioerger,...
This paper exploits the spatial representation of state space problem graphs to preprocess and enhance heuristic search engines. It combines classical AI exploration with computati...