Online research in philosophy

Examples involving common causes — most prominently, examples involving genetically influenced choices — are analytically equivalent not to standard Newcomb Problems — in which the Predictor genuinely predicts the agent's decision — but to non-standard Newcomb Problems — in which the Predictor guarantees the truth of her predictions by interfering with the agent's decision to make the agent choose as it was predicted she would. When properly qualified, causal and epistemic decision theories diverge only on standard — not on non-standard — Newcomb Problems, and thus not on examples involving common causes.

One of us (Eells 1982) has defended traditional evidential decision theory against prima facie Newcomb counterexamples by assuming that a common cause forms a conjunctive fork with its joint effects. In this paper, the evidential theory is defended without this assumption. The suggested rationale shows that the theory's assumptions are not about the nature of causality, but about the nature of rational deliberation. These presuppositions are weak enough for the argument to count as a strong justification of the evidential theory.

Proponents of causal decision theories argue that classical Bayesian decision theory (BDT) gives the wrong advice in certain types of cases, of which the clearest and commonest are the medical Newcomb problems. I defend BDT, invoking a familiar principle of statistical inference to show that in such cases a free agent cannot take the contemplated action to be probabilistically relevant to its causes (so that BDT gives the right answer). I argue that my defence does better than those of Ellery Eells and Richard Jeffrey; and that it applies, where necessary, to other types of Newcomb problem.

Andy Egan argues that neither evidential nor causal decision theory gives the intuitively right recommendation in the cases The Smoking Lesion, The Psychopath Button, and The Three-Option Smoking Lesion. Furthermore, Egan argues that we cannot avoid these problems by any kind of ratificationism. This paper develops a new version of ratificationism that gives the right recommendations. Thus, the new proposal has an advantage over evidential and casual decision theory and standard ratificationist evidential decision theory.

Nicholas Rescher claims that rational decision theory “may leave us in the lurch”, because there are two apparently acceptable ways of applying “the standard machinery of expected-value analysis” to his Dr. Psycho paradox which recommend contradictory actions. He detects a similar contradiction in Newcomb’s problem. We consider his claims from the point of view of both Bayesian decision theory and causal decision theory. In Dr. Psycho and in Newcomb’s Problem, Rescher has used premisses about probabilities which he assumes to be independent. From the former point of view, we show that the probability premisses are not independent but inconsistent, and their inconsistency is provable within probability theory alone. From the latter point of view, we show that their consistency can be saved, but then the contradictory recommendations evaporate. Consequently, whether one subscribes to evidential or causal decision theory, rational decision theory is not in any way vitiated by Rescher’s arguments.

In their development of causal decision theory, Allan Gibbard and William Harper advocate a particular method for calculating the expected utility of an action, a method based upon the probabilities of certain counterfactuals. Gibbard and Harper then employ their method to support a two-box solution to Newcomb’s paradox. This paper argues against some of Gibbard and Harper’s key claims concerning the truth-values and probabilities of counterfactuals involved in expected utility calculations, thereby disputing their analysis of Newcomb’s Paradox. If we are right, then Gibbard and Harper’s method of calculating expected utility does not adequately represent rational choice.

Richard Jeffrey long held that decision theory should be formulated without recourse to explicitly causal notions. Newcomb problems stand out as putative counterexamples to this ‘evidential’ decision theory. Jeffrey initially sought to defuse Newcomb problems via recourse to the doctrine of ratificationism, but later came to see this as problematic. We will see that Jeffrey’s worries about ratificationism were not compelling, but that valid ratificationist arguments implicitly presuppose causal decision theory. In later work, Jeffrey argued that Newcomb problems are not decisions at all because agents who face them possess so much evidence about correlations between their actions and states of the world that they are unable to regard their deliberate choices as causes of outcomes, and so cannot see themselves as making free choices. Jeffrey’s reasoning goes wrong because it fails to recognize that an agent’s beliefs about her immediately available acts are so closely tied to the immediate causes of these actions that she can create evidence that outweighs any antecedent correlations between acts and states. Once we recognize that deliberating agents are free to believe what they want about their own actions, it will be clear that Newcomb problems are indeed counterexamples to evidential decision theory.

After a brief presentation of evidential decision theory, causal decision theory, and Newcomb type prima facie counterexamples to the evidential theory, three kinds of "metatickle" defenses of the evidential theory are discussed. Each has its weaknesses, but one of them seems stronger than the other two. The weaknesses of the best of the three, and the intricacy of metatickle analysis, does not constitute an advantage of causal decision theory over the evidential theory, however. It is argued, by way of an example, that causal decision theory also stands in need of a metatickle defense.

This paper argues against evidential decision-theory, by showing that the newest responses to its biggest current problem – the medical Newcomb problems – don’t work. The latest approach is described, and the arguments of two main proponents of it – Huw Price and CR Hitchcock – clearly distinguished and examined. It is argued that since neither new defence is successful, causation remains essential to understanding means-end agency.

This paper looks at a dispute decision theory about how best to characterize expected utility maximization and express the logic of rational choice. Where A1, … , An are actions open to some particular agent, and S1, … , Sn are mutually exclusive states of the world such that the agent knows at least one of which obtains, does the logic of rational choice require an agent to consider the conditional probability of choice Ai given that some state Si obtains, Prob(Ai/Si). Or, is the logic of choice better represented by considering the probability of the counterfactual if Ai then Si, Prob(Ai ⟥-> Si). Causal decision theory, developed by Allan Gibbard, William Harper, and David Lewis defend the counterfactual analysis; whereas, Richard Jeffrey and others defend the conditional probability analysis, evidential decision theory. I argue that the problems posed by cases of decision instability favor evidential decision theory.