Results 1 
4 of
4
Foundations for Bayesian networks
, 2001
"... Bayesian networks are normally given one of two types of foundations: they are either treated purely formally as an abstract way of representing probability functions, or they are interpreted, with some causal interpretation given to the graph in a network and some standard interpretation of probabi ..."
Abstract

Cited by 11 (7 self)
 Add to MetaCart
Bayesian networks are normally given one of two types of foundations: they are either treated purely formally as an abstract way of representing probability functions, or they are interpreted, with some causal interpretation given to the graph in a network and some standard interpretation of probability given to the probabilities specified in the network. In this chapter I argue that current foundations are problematic, and put forward new foundations which involve aspects of both the interpreted and the formal approaches. One standard approach is to interpret a Bayesian network objectively: the graph in a Bayesian network represents causality in the world and the specified probabilities are objective, empirical probabilities. Such an interpretation founders when the Bayesian network independence assumption (often called the causal Markov condition) fails to hold. In §2 I catalogue the occasions when the independence assumption fails, and show that such failures are pervasive. Next, in §3, I show that even where the independence assumption does hold objectively, an agent’s causal knowledge is unlikely to satisfy the assumption with respect to her subjective probabilities, and that slight differences between an agent’s subjective Bayesian network and an objective Bayesian network can lead to large differences between probability distributions determined by these networks. To overcome these difficulties I put forward logical Bayesian foundations in §5. I show that if the graph and probability specification in a Bayesian network are thought of as an agent’s background knowledge, then the agent is most rational if she adopts the probability distribution determined by the
Causation in the special sciences: the case for pragmatism
 Stochastic Causality
, 2001
"... One of the jobs of philosophers of the special sciences is to connect the local concerns of particular disciplines with those of philosophy in general. The twoway complexities of this task are wellillustrated by the case of causation. On the one hand—from the outside, as it were— ..."
Abstract

Cited by 4 (1 self)
 Add to MetaCart
One of the jobs of philosophers of the special sciences is to connect the local concerns of particular disciplines with those of philosophy in general. The twoway complexities of this task are wellillustrated by the case of causation. On the one hand—from the outside, as it were—
Understanding of what engineers “do
 LSE Centre for Natural and Social Sciences, www.lse.ac.uk/Depts/cpnss/proj_causality.htm
, 2002
"... presented at ..."
THE ASYMMETRY OF INFLUENCE
"... Attempts to meddle with the past are futile. While this nugget of folk wisdom serves as a respectable guide to action, its utility is standardly conceived as arising from the general inability of anything to influence the past. This explanation, though, oversimplifies the complex architecture of fac ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
Attempts to meddle with the past are futile. While this nugget of folk wisdom serves as a respectable guide to action, its utility is standardly conceived as arising from the general inability of anything to influence the past. This explanation, though, oversimplifies the complex architecture of fact and fiction responsible for the reasonableness of not trying