We introduce a family of rules for adjusting one's credences in response to learning the credences of others. These rules have a number of desirable features. 1. They yield the posterior credences that would result from updating by standard Bayesian conditionalization on one's peers' reported credences if one's likelihood function takes a particular simple form. 2. In the simplest form, they are symmetric among the agents in the group. 3. They map neatly onto the familiar Condorcet voting results. 4. They (...) preserve shared agreement about independence in a wide range of cases. 5. They commute with conditionalization and with multiple peer updates. Importantly, these rules have a surprising property that we call synergy - peer testimony of credences can provide mutually supporting evidence raising an individual's credence higher than any peer's initial prior report. At first, this may seem to be a strike against them. We argue, however, that synergy is actually a desirable feature and the failure of other updating rules to yield synergy is a strike against them. (shrink)

In their article 'Causes and Explanations: A Structural-Model Approach. Part I: Causes', Joseph Halpern and Judea Pearl draw upon structural equation models to develop an attractive analysis of 'actual cause'. Their analysis is designed for the case of deterministic causation. I show that their account can be naturally extended to provide an elegant treatment of probabilistic causation.

This Element provides an accessible introduction to the contemporary philosophy of causation. It introduces the reader to central concepts and distinctions and to key tools drawn upon in the contemporary debate. The aim is to fuel the reader's interest in causation, and to equip them with the resources to contribute to the debate themselves. The discussion is historically informed and outward-looking. 'Historically informed' in that concise accounts of key historical contributions to the understanding of causation set the stage for an (...) examination of the latest research. 'Outward looking' in that illustrations are provided of how the philosophy of causation relates to issues in the sciences, law, and elsewhere. The aim is to show why the study of causation is of critical importance, besides being fascinating in its own right. (shrink)

ABSTRACT Joseph Halpern and Judea Pearl draw upon structural equation models to develop an attractive analysis of ‘actual cause’. Their analysis is designed for the case of deterministic causation. I show that their account can be naturally extended to provide an elegant treatment of probabilistic causation. 1Introduction 2Preemption 3Structural Equation Models 4The Halpern and Pearl Definition of ‘Actual Cause’ 5Preemption Again 6The Probabilistic Case 7Probabilistic Causal Models 8A Proposed Probabilistic Extension of Halpern and Pearl’s Definition 9Twardy and Korb’s Account 10Probabilistic (...) Fizzling 11Conclusion. (shrink)

We investigate whether standard counterfactual analyses of causation imply that the outcomes of space-like separated measurements on entangled particles are causally related. Although it has sometimes been claimed that standard CACs imply such a causal relation, we argue that a careful examination of David Lewis’s influential counterfactual semantics casts doubt on this. We discuss ways in which Lewis’s semantics and standard CACs might be extended to the case of space-like correlations.

Special science generalizations admit of exceptions. Among the class of non-exceptionless special science generalizations, I distinguish minutis rectis generalizations from the more familiar category of ceteris paribus generalizations. I argue that the challenges involved in showing that mr generalizations can play the law role are underappreciated, and quite different from those involved in showing that cp generalizations can do so. I outline a strategy for meeting the challenges posed by mr generalizations.

Much recent philosophical attention has been devoted to the prospects of the Best System Analysis of chance for yielding high-level chances, including statistical mechanical and special science chances. But a foundational worry about the BSA lurks: there don’t appear to be uniquely correct measures of the degree to which a system exhibits theoretical virtues, such as simplicity, strength, and fit. Nor does there appear to be a uniquely correct exchange rate at which the theoretical virtues trade off against one another (...) in the determination of an overall best system. I argue that there’s no robustly best system for our world – no system that comes out best under every reasonable measure of the theoretical virtues and exchange rate between them – but rather a set of ‘tied-for-best’ systems: a set of very good systems, none of which is robustly best. Among the tied-for-best systems are systems that entail differing high-level probabilities. I argue that the advocate of the BSA should conclude that the high-level chances for our world are imprecise. (shrink)

Much recent philosophical attention has been devoted to variants on the Best System Analysis of laws and chance. In particular, philosophers have been interested in the prospects of such Best System Analyses for yielding *high-level* laws and chances. Nevertheless, a foundational worry about BSAs lurks: there do not appear to be uniquely appropriate measures of the degree to which a system exhibits theoretical virtues, such as simplicity and strength. Nor does there appear to be a uniquely correct exchange rate at (...) which the theoretical virtues of simplicity, strength, and likelihood trade off against one another in the determination of a best system. Moreover, it may be that there is no *robustly* best system: no system that comes out best under *any* reasonable measures of the theoretical virtues and exchange rate between them. This worry has been noted by several philosophers, with some arguing that there is indeed plausibly a set of tied-for-best systems for our world. Some have even argued that this entails that there are no Best System laws or chances in our world. I argue that, while it *is* plausible that there is a set of tied-for-best systems for our world, it doesn't follow from this that there are no Best System chances. Rather, it follows that the Best System chances for our world are *unsharp*. (shrink)