In Newcomb’s paradox you can choose to receive either the contents of a particular closed box, or the contents of both that closed box and another one. Before you choose though, an antagonist uses a prediction algorithm to accurately deduce your choice, and uses that deduction to fill the two boxes. The way they do this guarantees that you made the wrong choice. Newcomb’s paradox is that game theory’s expected utility and dominance principles appear to provide conflicting recommendations for what (...) you should choose. Here we show that the conflicting recommendations assume different probabilistic structures relating your choice and the algorithm’s prediction. This resolves the paradox: the reason there appears to be two conflicting recommendations is that the probabilistic structure relating the problem’s random variables is open to two, conflicting interpretations. We then show that the accuracy of the prediction algorithm in Newcomb’s paradox, the focus of much previous work, is irrelevant. We end by showing that Newcomb’s paradox is time-reversal invariant; both the paradox and its resolution are unchanged if the algorithm makes its ‘prediction’ after you make your choice rather than before. (shrink)

A fully adequate solution to Newcomb’s Problem (Nozick 1969) should reveal the source of its extraordinary elusiveness and persistent intractability. Recently, a few accounts have independently sought to meet this criterion of adequacy by exposing the underlying source of the problem’s profound puzzlement. Thus, Sorensen (1987), Slezak (1998), Priest (2002) and Maitzen and Wilson (2003) share the ‘no box’ view according to which the very idea that there is a right choice is misconceived since the problem is ill-formed or incoherent (...) in some way. Among proponents of this view, Richard Jeffrey (2004) recently declared that he renounces his earlier position that accepted Newcomb problems as genuine decision problems. Significantly, Jeffrey suggests that “Newcomb problems are like Escher’s famous staircase on which an unbroken ascent takes you back where you started” (Jeffrey (2004; 113)). Jeffrey’s analogy is apt for a puzzle whose specific logical features can be precisely articulated. Along the lines of these related approaches, I propose to improve and clarify them by providing such a deeper analysis that elucidates their essential, related insights. (shrink)

The 'Why ain'cha rich?' argument for one-boxing in Newcomb's problem allegedly vindicates evidential decision theory and undermines causal decision theory. But there is a good response to the argument on behalf of causal decision theory. I develop this response. Then I pose a new problem and use it to give a new 'Why ain'cha rich?' argument. Unlike the old argument, the new argument targets evidential decision theory. And unlike the old argument, the new argument is sound.

This paper aims to make three contributions to decision theory. First there is the hope that it will help to re-establish the legitimacy of the problem, pace various recent analyses provided by Maitzen and Wilson, Slezak and Priest. Second, after pointing out that analyses of the problem have generally relied upon evidence that is conditional on the taking of one particular option, this paper argues that certain assumptions implicit in those analyses are subtly flawed. As a third contribution, the piece (...) aims to draw attention to an important similarity between Newcomb’s problem and the toxin puzzle. In short, both problems illustrate the fact that you can have a reason to intend to φ without having a reason to actually φ. (shrink)

Concrete Causation centers about theories of causation, their interpretation, and their embedding in metaphysical-ontological questions, as well as the application of such theories in the context of science and decision theory. The dissertation is divided into four chapters, that firstly undertake the historical-systematic localization of central problems (chapter 1) to then give a rendition of the concepts and the formalisms underlying David Lewis' and Judea Pearl's theories (chapter 2). After philosophically motivated conceptual deliberations Pearl's mathematical-technical framework is drawn on for (...) an epistemic interpretation and for emphasizing the knowledge-organizing aspect of causality in an extension of the interventionist Bayes net account of causation (chapter 3). Integrating causal and non-causal knowledge in unified structures ultimately leads to an approach towards solving problems of (causal) decision theory and at the same time facilitates the representation of logical-mathematical, synonymical, as well as reductive relationships in efficiently structured, operational nets of belief propagation (chapter 4). (shrink)

Newcomb’s problem is viewed as a dynamic game with an agent and a superior being as players. Depending on whether or not a risk-neutral agent’s confidence in the superior being, as measured by a subjective probability assigned to the move order, exceeds a threshold or not, one obtains the one-box outcome or the two-box outcome, respectively. The findings are extended to an agent with arbitrary increasing utility, featuring in general two thresholds. All solutions require only minimal assumptions about the being’s (...) payoffs, and the being is always sure to predict the agent’s choice in equilibrium. The relevant Nash equilibria are subgame-perfect, except for risk-seeking agents where for intermediate beliefs, the being may be unable to ensure perfect prediction without relying on noncredible threats. Lastly, analogies of Newcomb’s problem to the commitment problem on a continuum are discussed. (shrink)