Subjunctive conditionals are fundamental to rational decision both in single agent and multiple agent decision problems. They need explicit analysis only when they cause problems, as they do in recent discussions of rationality in extensive form games. This paper examines subjunctive conditionals in the theory of games using a strict revealed preference interpretation of utility. Two very different models of games are investigated, the classical model and the limits of reality model. In the classical model the logic of backward induction is valid, but it does not use subjunctive conditionals; the relevant subjunctive conditionals do not even make sense. In the limits of reality model the subjunctive conditionals do make sense but backward induction is valid only under special assumptions.

The pragmatic character of the Dutch book argument makes it unsuitable as an “epistemic” justification for the fundamental probabilist dogma that rational partial beliefs must conform to the axioms of probability. To secure an appropriately epistemic justification for this conclusion, one must explain what it means for a system of partial beliefs to accurately represent the state of the world, and then show that partial beliefs that violate the laws of probability are invariably less accurate than they could be otherwise. The first task can be accomplished once we realize that the accuracy of systems of partial beliefs can be measured on a gradational scale that satisfies a small set of formal constraints, each of which has a sound epistemic motivation. When accuracy is measured in this way it can be shown that any system of degrees of belief that violates the axioms of probability can be replaced by an alternative system that obeys the axioms and yet is more accurate in every possible world. Since epistemically rational agents must strive to hold accurate beliefs, this establishes conformity with the axioms of probability as a norm of epistemic rationality whatever its prudential merits or defects might be.

Ever since Berkeley discussed the problem at length in his Essay Toward a New Theory of Vision, theorists of vision have attempted to explain why the moon appears larger on the horizon than it does at the zenith. Prevailing opinion has it that the contemporary perceptual psychologists Kaufman and Rock have finally explained the illusion. This paper argues that Kaufman and Rock have not refuted a Berkeleyan account of the illusion, and have over-interpreted their own experimental results. The moon illusion remains unexplained, and a Berkeleyan account is still a contender.

The use of idealized models in science is by now well-documented. Such models are typically constructed in a “top-down” fashion: starting with an intractable theory or law and working down toward the phenomenon. This view of model-building has motivated a family of confirmation schemes based on the convergence of prediction and observation. This paper considers how chaotic dynamics blocks the convergence view of confirmation and has forced experimentalists to take a different approach to model-building. A method known as “phase space reconstruction” not only reveals a lacuna in the philosophical literature on models, it also fails to conform to conventional views about how models are used to confirm a theory.

I use an explanation of Yanomami warfare given by the anthropologist Brian Ferguson as a case study to compare the merits of the causal and unification approaches to explanation. I argue that Ferguson's insistence on explaining actual occurrences and patterns of Yanomami warfare together with his claim that all of his generalizations are statistical raises difficulties for the unification approach, because of its commitment to “deductive chauvinism.” Moreover, I show that there are serious difficulties involved in comparing the “unifying power” of Ferguson's explanations to those of his competitors. I show that the causal approach can provide a rich analysis of Ferguson's explanation while avoiding these difficulties.

Daniel Steel argues that a causal theory of explanation can account for Ferguson's anthropological theory of Yanomami warfare but that a unification theory of explanation cannot. I argue that a unification theory can explain such an account, in a manner similar to Hempel's view of explanation in history. I go on to argue that the unification theory allows for different explanations of specific and general social circumstances.

Why does classical equilibrium statistical mechanics work? Malament and Zabell (1980) noticed that, for ergodic dynamical systems, the unique absolutely continuous invariant probability measure is the microcanonical. Earman and Rédei (1996) replied that systems of interest are very probably not ergodic, so that absolutely continuous invariant probability measures very distant from the microcanonical exist. In response I define the generalized properties of epsilon-ergodicity and epsilon-continuity, I review computational evidence indicating that systems of interest are epsilon-ergodic, I adapt Malament and Zabell's defense of absolute continuity to support epsilon-continuity, and I prove that, for epsilon-ergodic systems, every epsilon-continuous invariant probability measure is very close to the microcanonical.