This paper examines Wesley Salmon's "process" theory of causality, arguing in particular that there are four areas of inadequacy. These are that the theory is circular, that it is too vague at a crucial point, that statistical forks do not serve their intended purpose, and that Salmon has not adequately demonstrated that the theory avoids Hume's strictures about "hidden powers". A new theory is suggested, based on "conserved quantities", which fulfills Salmon's broad objectives, and which avoids the problems discussed.

Entropy is ubiquitous in physics, and it plays important roles in numerous other disciplines ranging from logic and statistics to biology and economics. However, a closer look reveals a complicated picture: entropy is defined differently in different contexts, and even within the same domain different notions of entropy are at work. Some of these are defined in terms of probabilities, others are not. The aim of this chapter is to arrive at an understanding of some of the most important notions (...) of entropy and to clarify the relations between them, After setting the stage by introducing the thermodynamic entropy, we discuss notions of entropy in information theory, statistical mechanics, dynamical systems theory and fractal geometry. (shrink)

This paper reviews four attempts throughout the history of quantum mechanics to explicitly employ dispositional notions in order to solve the quantum paradoxes, namely: Margenau's latencies, Heisenberg's potentialities, Maxwell's propensitons, and the recent selective propensities interpretation of quantum mechanics. Difficulties and challenges are raised for all of them, and it is concluded that the selective propensities approach nicely encompasses the virtues of its predecessors. Finally, some strategies are discussed for reading similar dispositional notions into two other well-known interpretations of quantum (...) mechanics, namely the GRW interpretation and Bohmian mechanics. (shrink)

According to principles of probability coordination, such as Miller's Principle or Lewis's Principal Principle, you ought to set your subjective probability for an event equal to what you take to be the objective probability of the event. For example, you should expect events with a very high probability to occur and those with a very low probability not to occur. This paper examines the grounds of such principles. It is argued that any attempt to justify a principle of probability coordination (...) encounters the same difficulties as attempts to justify induction. As a result, no justification can be found. (shrink)

Reichenbach sought to resolve Hume's problem of the justification of induction by means of a pragmatic vindication that relies heavily on the convergence properties of his rule of induction. His attempt to rule out all other asymptotic methods by an appeal to descriptive simplicity was unavailing. We found that important progress in that direction could be made by invoking normalizing conditions (consistency) and methodological simplicity (as a basis for invariance), but that they did not do the whole job. I am (...) proposing that, in the end, Reichenbach's own distinction between discovery and justification holds the key to the solution. (shrink)

Single-case and long-run propensity theories are among the main objective interpretations of probability. There have been various objections to these theories, e.g. that it is difficult to explain why propensities should satisfy the probability axioms and, worse, that propensities are at odds with these axioms, that the explication of propensities is circular and accordingly not informative, and that single-case propensities are metaphysical and accordingly non-scientific. We consider various propensity theories of probability and their prospects in light of these objections. We (...) argue that while propensity theories face challenges, these challenges do not undermine their validity as prospective interpretations of probability in science. (shrink)

I analyse critically what I regard as the most accomplished empiricist account of propensities, namely the long run propensity theory developed by Donald Gillies . Empiricist accounts are distinguished by their commitment to the ‘identity thesis’: the identification of propensities and objective probabilities. These theories are intended, in the tradition of Karl Popper’s influential proposal, to provide an interpretation of probability that renders probability statements directly testable by experiment. I argue that the commitment to the identity thesis leaves empiricist theories, (...) including Gillies’ version, vulnerable to a variant of what is known as Humphreys’ paradox. I suggest that the tension may be resolved only by abandoning the identity thesis, and by adopting instead an understanding of propensities as explanatory properties of chancy objects. (shrink)

I define a concept of causal probability and apply it to questions about the role of probability in evolutionary processes. Causal probability is defined in terms of manipulation of patterns in empirical outcomes by manipulating properties that realize objective probabilities. The concept of causal probability allows us see how probabilities characterized by different interpretations of probability can share a similar causal character, and does so in such way as to allow new inferences about relationships between probabilities realized in different chance (...) setups. I clarify relations between probabilities and properties defined in terms of them, and argue that certain widespread uses of computer simulations in evolutionary biology show that many probabilities relevant to evolutionary outcomes are causal probabilities. This supports the claim that higher-level properties such as biological fitness and processes such as natural selection are causal properties and processes, contrary to what some authors have argued. (shrink)

These are the introduction chapters to the forthcoming collection of essays published by Springer (Synthese Library) and entitled Probabilities, Causes and Propensities in Physics.

The objective of this paper is to show that, instead of quantum probabilities, wave packets are physically real. First, Cartwright's recent argument for the reality of quantum probabilities is criticized. Then, the notion of ‘physically real’ is precisely defined and the difference between wave functions and quantum probabilities clarified. Being thus prepared, some strong reasons are discussed for considering the wave packet to be physically real. Finding the reasons inconclusive, I explain how the Aharonov—Bohm effect delivers the final punch. I (...) conclude that wave packets are the quantum objects that underlie the indeterministic quantum processes and have the propensity of displaying probabilistic (or indeterministic) behavior. (shrink)

The aim of this paper is to distinguish between, and examine, three issues surrounding Humphreys's paradox and interpretation of conditional propensities. The first issue involves the controversy over the interpretation of inverse conditional propensities — conditional propensities in which the conditioned event occurs before the conditioning event. The second issue is the consistency of the dispositional nature of the propensity interpretation and the inversion theorems of the probability calculus, where an inversion theorem is any theorem of probability that makes explicit (...) (or implicit) appeal to a conditional probability and its corresponding inverse conditional probability. The third issue concerns the relationship between the notion of stochastic independence which is supported by the propensity interpretation, and various notions of causal independence. In examining each of these issues, it is argued that the dispositional character of the propensity interpretation provides a consistent and useful interpretation of the probability calculus. (shrink)

I review five explicit attempts throughout the history of quantum mechanics to invoke dispositional notions in order to solve the quantum paradoxes, namely: Margenau’s latencies, Heisenberg’s potentialities, Popper’s propensity interpretation of probability, Nick Maxwell’s propensitons, and the recent selective propensities interpretation of quantum mechanics. I raise difficulties and challenges for all of them, but conclude that the selective propensities approach nicely encompasses the virtues of its predecessors. I elaborate on some of the properties of the type of propensities that I (...) claim to be successful for quantum mechanics, and finish by briefly sketching out ways in which similar notions can be read into some of the other well-known interpretations of quantum mechanics. (shrink)

As common experience confirms, procrastination seems not only possible, but widespread. However, procrastination should not be taken for granted. Often, the procrastinator harms herself knowingly. It thus clearly seems that such a person lacks the self-concern that usually characterises us. After having spelled out what procrastination is, and having explored its main varieties, I consider the relation between procrastination and risk-taking. After this, I discuss the implications of this phenomenon for the debates about personal identity. The upshot, I argue, is (...) that reductionist accounts, according to which identity is a matter of psychological continuity, are in a better position as might have been thought. (shrink)

Probability as understood today, namely as a quantitative notion expressible by means of a function ranging in the interval between 0–1, took shape in the mid-17th century, and presents both a mathematical and a philosophical aspect. Of these two sides, the second is by far the most controversial, and fuels a heated debate, still ongoing. After a short historical sketch of the birth and developments of probability, its major interpretations are outlined, by referring to the work of their most prominent (...) representatives. The final section addresses the question of whether any of such interpretations can presently be considered predominant, which is answered in the negative. (shrink)

I argue that categorical realism, contrary to what most believe today, holds for quantum (and indeed for all) objects and substances. The main argument consists of two steps: (i) the recent experimental verification of the AB effect gives strong empirical evidence for taking quantum potentials as physically real (or substantival), which suggests a change of the data upon which any viable interpretation of quantum theory must rely, and (ii) quantum potentials may be consistently taken as the categorical properties of quantum (...) objects so that categorical realism can be restored. (shrink)

This paper outlines a general theory of efficient causation, a theory that deals in a unified way with traditional or deterministic, indeterministic, probabilistic, and other causal concepts. Theorists like Lewis, Salmon, and Suppes have attempted to broaden our causal perspective by reductively analysing causal notions in other terms. By contrast, the present theory rests in the first place on a non-reductive analysis of traditional causal concepts — into formal or structural components, on the one hand, and a physical or metaphysical (...) component, on the other. The analyzans is then generalised. The theory also affords a more general propensity notion than is standard, one that helps solve major problems facing propensity interpretations of probability. (shrink)

This paper investigates the relations between causality and propensity. Aparticular version of the propensity theory of probability is introduced, and it is argued that propensities in this sense are not causes. Some conclusions regarding propensities can, however, be inferred from causal statements, but these hold only under restrictive conditions which prevent cause being defined in terms of propensity. The notion of a Bayesian propensity network is introduced, and the relations between such networks and causal networks is investigated. It is argued (...) that causal networks cannot be identified with Bayesian propensity networks, but that causal networks can be a valuable heuristic guide for the construction of Bayesian propensity networks. (shrink)