In this paper, we develop and evaluate several probabilistic models of user click-through behavior that are appropriate for modeling the click-through rates of items that are pres...
Hila Becker, Christopher Meek, David Maxwell Chick...
This paper presents a method for learning a semantic parser from ambiguous supervision. Training data consists of natural language sentences annotated with multiple potential mean...
Currently, among the fastest approaches to AI task planning we find many forward-chaining heuristic planners, as FF. Most of their good performance comes from the use of domain-i...
We describe an algorithm and experiments for inference of edge replacement graph grammars. This method generates candidate recursive graph grammar productions based on isomorphic ...
Jacek P. Kukluk, Lawrence B. Holder, Diane J. Cook
POMDPs are a popular framework for representing decision making problems that contain uncertainty. The high computational complexity of finding exact solutions to POMDPs has spaw...