Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...
Machine learning methods are frequently used to create rule-based classifiers. For continuous features linguistic variables used in conditions of the rules are defined by membershi...
Wlodzislaw Duch, Norbert Jankowski, Krzysztof Grab...
To coordinate with other agents in its environment, an agent needs models of what the other agents are trying to do. When communication is impossible or expensive, this informatio...
Marcus J. Huber, Edmund H. Durfee, Michael P. Well...
We present a new approach for finding generalized contingent plans with loops and branches in situations where there is uncertainty in state properties and object quantities, but ...
Siddharth Srivastava, Neil Immerman, Shlomo Zilber...
This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of t...