The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
A new approach for constructing pseudo-keywords, referred to as Sense Units, is proposed. Sense Units are obtained by a word clustering process, where the underlying similarity re...
Supervised and unsupervised learning methods have traditionally focused on data consisting of independent instances of a single type. However, many real-world domains are best des...
Neural Logic Network or Neulonet is a hybrid of neural network expert systems. Its strength lies in its ability to learn and to represent human logic in decision making using comp...
We consider an on-line decision-theoretic interpreter and incremental execution of Golog programs. This new interpreter is intended to overcome some limitations of the off-line in...
In this paper we describe a multiagent system in which agents negotiate to allocate resources and satisfy constraints in a real-time environment of multisensor target tracking. Th...
We study the impact of backbones in optimization and approximation problems. We show that some optimization problems like graph coloring resemble decision problems, with problem h...
We present an extensive experimental study of consequence-finding algorithms based on kernel resolution, using both a trie-based and a novel ZBDD-based implementation, which uses ...
Groundedmodels(Siena2001b)differ fromaxiomatictheories in establishingexplicit connectionsbetweenlanguage andreality that are learnedthroughlanguagegames(Wittgenstein 1953).Thispa...