In our research we study rational agents which learn how to choose the best conditional, partial plan in any situation. The agent uses an incomplete symbolic inference engine, emp...
We show how linear typing can be used to obtain functional programs which modify heap-allocated data structures in place. We present this both as a "design pattern" for ...
Higher-Order Fixpoint Logic (HFL) is a hybrid of the simply typed λ-calculus and the modal µ-calculus. This makes it a highly expressive temporal logic that is capable of express...
The classification of encrypted traffic on the fly from network traces represents a particularly challenging application domain. Recent advances in machine learning provide the opp...
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...