61 search results - page 3 / 13 » Automated Learning of Probabilistic Assumptions for Composit... |
DLOG
1998
13 years 6 months ago
1998
This paper proposes a framework to learn concepts from di erent kinds of observations. We de ne a language to describe meta-concepts, that represent the sets of possible concepts ...
CAV
2005
Springer
13 years 11 months ago
2005
Springer
Abstract. We address the issue of efficiently automating assume-guarantee reasoning for simulation conformance between finite state systems and specifications. We focus on a non...
ILP
2007
Springer
13 years 11 months ago
2007
Springer
Research over the past several decades in learning logical and probabilistic models has greatly increased the range of phenomena that machine learning can address. Recent work has ...
ICLP
2009
Springer
14 years 6 months ago
2009
Springer
PRISM is a probabilistic extension of Prolog. It is a high level language for probabilistic modeling capable of learning statistical parameters from observed data. After reviewing ...
KR
2004
Springer
13 years 10 months ago
2004
Springer
To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...