Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections (...) and statistical associations. Cited in more than 2,100 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. In this revised edition, Judea Pearl elucidates thorny issues, answers readers' questions, and offers a panoramic view of recent advances in this field of research. Causality will be of interest to students and professionals in a wide variety of fields. Dr Judea Pearl has received the 2011 Rumelhart Prize for his leading research in Artificial Intelligence and systems from The Cognitive Science Society. (shrink)

This book is a defense of modal realism; the thesis that our world is but one of a plurality of worlds, and that the individuals that inhabit our world are only a few out of all the inhabitants of all the worlds. Lewis argues that the philosophical utility of modal realism is a good reason for believing that it is true.

Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.

Ever since David Hume, empiricists have barred powers and capacities from nature. In this book Cartwright argues that capacities are essential in our scientific world, and, contrary to empiricist orthodoxy, that they can meet sufficiently strict demands for testability. Econometrics is one discipline where probabilities are used to measure causal capacities, and the technology of modern physics provides several examples of testing capacities (such as lasers). Cartwright concludes by applying the lessons of the book about capacities and probabilities to the (...) explanation of the role of causality in quantum mechanics. (shrink)

It has been the dominant view that probabilistic explanations of particular facts must be inductive in character. I argue here that this view is mistaken, and that the aim of probabilistic explanation is not to demonstrate that the explanandum fact was nomically expectable, but to give an account of the chance mechanism(s) responsible for it. To this end, a deductive-nomological model of probabilistic explanation is developed and defended. Such a model has application only when the probabilities occurring in covering laws (...) can be interpreted as measures of objective chance, expressing the strength of physical propensities. Unlike inductive models of probabilistic explanation, this deductive model stands in no need of troublesome requirements of maximal specificity or epistemic relativization. (shrink)

Recently several thought experiments have been developed (by John Carroll amongst others) which have been alleged to refute the Ramsey-Lewis view of laws of nature. The paper aims to show that two such thought experiments fail to establish that the Ramsey-Lewis view is false, since they presuppose a conception of laws of nature that is radically at odds with the Humean conception of laws embodied by the Ramsey-Lewis view. In particular, the thought experiments presuppose that laws of nature govern the (...) behavior of objects. The paper argues that the claim that laws govern should not be regarded as a conceptual truth, and shows how the governing conception of laws manifests itself in the thought experiments. Hence the thought experiments do not constitute genuine counter-examples to the Ramsey-Lewis view. since the Humean is free to reject the conception of laws which the thought experiments presuppose. (shrink)

Causation is a central topic in many areas of philosophy. In metaphysics, philosophers want to know what causation is, and how it is related to laws of nature, probability, action, and freedom of the will. In epistemology, philosophers investigate how causal claims can be inferred from statistical data, and how causation is related to perception, knowledge and explanation. In the philosophy of mind, philosophers want to know whether and how the mind can be said to have causal efficacy, and in (...) ethics, whether there is a moral distinction between acts and omissions and whether the moral value of an act can be judged according to its consequences. And causation is a contested concept in other fields of enquiry, such as biology, physics, and the law. This book provides an in-depth and comprehensive overview of these and other topics, as well as the history of the causation debate from the ancient Greeks to the logical empiricists. The chapters provide surveys of contemporary debates, while often also advancing novel and controversial claims; and each includes a comprehensive bibliography and suggestions for further reading. The book is thus the most comprehensive source of information about causation currently available, and will be invaluable for upper-level undergraduates through to professional philosophers. (shrink)

This is the second volume of philosophical essays by one of the most innovative and influential philosophers now writing in English. Containing thirteen papers in all, the book includes both new essays and previously published papers, some of them with extensive new postscripts reflecting Lewis's current thinking. The papers in Volume II focus on causation and several other closely related topics, including counterfactual and indicative conditionals, the direction of time, subjective and objective probability, causation, explanation, perception, free will, and rational (...) decision. Throughout, Lewis analyzes global features of the world in such a way as to show that they might turn out to supervene on the spatiotemporal arrangement of local qualities. (shrink)

In his recent work, Michael Redhead (1986, 1987, 1989, 1990) has introduced a condition he calls robustness which, he argues, a relation must satisfy in order to be causal. He has used this condition to argue further that EPR-type correlations are neither the result of a direct causal connection between the correlated events, nor the result of a common cause associated with the source of the particle pairs which feature in these events. Andrew Elby (1992) has used this same condition (...) as a premise in an independent argument for the conclusion that EPR-type correlations cannot be causally explained (except, perhaps, by a nonlocal hidden variable theory). I wish to argue here that robustness is itself too fragile a notion to support such conclusions. (shrink)

In this book, J. L. Mackie makes a careful study of several philosophical issues involved in his account of causation. Mackie follows Hume's distinction between causation as a concept and causation as it is ‘in the objects’ and attempts to provide an account of both aspects. Mackie examines the treatment of causation by philosophers such as Hume, Kant, Mill, Russell, Ducasse, Kneale, Hart and Honore, and von Wright. Mackie's own account involves an analysis of causal statements in terms of counterfactual (...) conditionals though these are judged to be incapable of giving a complete account of causation. Mackie argues that regularity theory too can only offer an incomplete picture of the nature of causation. In the course of his analysis, Mackie critically examines the account of causation offered by Kant, as well as the contemporary Kantian approaches offered by philosophers such as Bennett and Strawson. Also addressed are issues such as the direction of causation, the relation of statistical laws and functional laws, the role of causal statements in legal contexts, and the understanding of causes both as ‘facts’ and ‘events’. Throughout the discussion of these topics, Mackie develops his own complex account of the nature of causation, finally bringing his analysis to bear in regard to the topic of teleology and the question of whether final causes can be justifiably reduced to efficient causes. (shrink)

John Foster; VI*—Induction, Explanation and Natural Necessity, Proceedings of the Aristotelian Society, Volume 83, Issue 1, 1 June 1983, Pages 87–102, https://d.

I want to examine a possible solution to the problem of induction-one which, as far as I know, has not been discussed elsewhere. The solution makes crucial use of the notion of objective natural necessity. For the purposes of this discussion, I shall assume that this notion is coherent. I am aware that this assumption is controversial, but I do not have space to examine the issue here.

Using three intuitive notions about causes, including Redhead's robustness condition, I formulate necessary conditions on partial causes. I then demonstrate that we cannot explain the EPR correlations in terms of partial causes unless we abandon the quantum mechanical framework and adopt a nonlocal hidden-variable theory. The argument, unlike its predecessors, does not appeal to relativity theory.

Clark Glymour, Richard Scheines, Peter Spirtes and Kevin Kelly. Discovering Causal Structure: Artifical Intelligence, Philosophy of Science and Statistical Modeling.