We present a new estimator for counting the number of solutions of a Boolean satisfiability problem as a part of an importance sampling framework. The estimator uses the recently...
Models of crowd behavior facilitate analysis and prediction of human group behavior, where people are affected by each other’s presence. Unfortunately, existing models leave man...
Automation of Web service composition is one of the most interesting challenges facing the Semantic Web today. In this paper we propose a mean of performing automated Web service ...
Often remote investigations use autonomous agents to observe an environment on behalf of absent scientists. Predictive exploration improves these systems’ efficiency with onboa...
Since Bayesian network (BN) was introduced in the field of artificial intelligence in 1980s, a number of inference algorithms have been developed for probabilistic reasoning. Ho...
We introduce a new method for finding nodes semantically related to a given node in a hyperlinked graph: the Green method, based on a classical Markov chain tool. It is generic, ...
Reciprocity is a key determinant of human behavior and has been well documented in the psychological and behavioral economics literature. This paper shows that reciprocity has sig...
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...
The paper presents and evaluates the power of best-first search over AND/OR search spaces in graphical models. The main virtue of the AND/OR representation is its sensitivity to ...