Acquisition of Causal Models for Local Distributions in Bayesian Networks

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Local Characterizations of Causal Bayesian Networks

The standard definition of causal Bayesian networks (CBNs) invokes a global condition according to which the distribution resulting from any intervention can be decomposed into a truncated product dictated by its respective mutilated subgraph. We analyze alternative formulations which emphasizes local aspects of the causal process and can serve therefore as more meaningful criteria for coherenc...

متن کامل

Using Causal Information and Local Measures to Learn Bayesian Networks

In previous work we developed a method of learning Bayesian Network models from raw data This method relies on the well known minimal description length MDL principle The MDL principle is particularly well suited to this task as it allows us to tradeo in a principled way the accuracy of the learned network against its practical usefulness In this paper we present some new results that have aris...

متن کامل

A software system for causal reasoning in causal Bayesian networks

Knowing the cause and effect is important to researchers who are interested in modeling the effects of actions, and Artificial Intelligence researchers are among them. One commonly used method for modeling cause and effect is graphical model. Bayesian Network is a probabilistic graphical model for representing and reasoning uncertain knowledge. It has been used as a fundamental tool and is beco...

متن کامل

Causal Interaction in Bayesian Networks

Artificial Intelligence (AI) and Philosophy of Science share a fundamental problem—that of understanding causality. Bayesian network techniques have recently been used by Judea Pearl in a new approach to understanding causality and causal processes (Pearl, 2000). Pearl’s approach has great promise, but needs to be supplemented with an explicit account of causal interaction. Thus far, despite co...

متن کامل

Causal reversibility in Bayesian networks

Causal manipulation theorems proposed by Spirtes et al. and Pearl in the context of directed probabilistic graphs, such as Bayesian networks, oŒer a simple and theoretically sound formalism for predicting the eŒect of manipulation of a system from its causal model. While the theorems are applicable to a wide variety of equilibrium causal models, they do not address the issue of reversible causa...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Transactions on Cybernetics

سال: 2014

ISSN: 2168-2267,2168-2275

DOI: 10.1109/tcyb.2013.2290775