Paul Weirich

Causal decision theory produces decision instability in cases such as Death in Damascus where a decision itself provides evidence concerning the utility of options. Several authors have proposed ways of handling this instability. William Harper (1985 and 1986) advances one of the most elegant proposals. He recommends maximizing causal expected utility among the options that are causally ratifiable. Unfortunately, Harper's proposal imposes certain restrictions; for instance, the restriction that mixed strategies are freely available. To obtain a completely general method of handling decision instability, I step outside the confines of pure causal decision theory. I introduce a new kind of backtracking expected utility and propose maximizing it among the options that are causally ratifiable. In other words, I propose a hierarchical maximization of (1) conditional causal expected utility and (2) the new backtracking expected utility. I support this proposal with some intuitive considerations concerning the distinction between optimality and conditional optimality. And I prove that the proposal yields a solution in every finite decision problem

The conditional probability of h given e is commonly claimed to be equal to the probability that h would have if e were learned. Here I contend that this general claim about conditional probabilities is false. I present a counter-example that involves probabilities of probabilities, a second that involves probabilities of possible future actions, and a third that involves probabilities of indicative conditionals. In addition, I briefly defend these counter-examples against charges that the probabilities they involve are illegitimate

The rule to maximize expected utility is intended for decisions where options involve risk. In those decisions the decision maker's attitude toward risk is important, and the rule ought to take it into account. Allais's and Ellsberg's paradoxes, however, suggest that the rule ignores attitudes toward risk. This suggestion is supported by recent psychological studies of decisions. These studies present a great variety of cases where apparently rational people violate the rule because of aversion or attraction to risk. Here I attempt to resolve the issue concerning expected utility and risk. I distinguish two versions of the rule to maximize expected utility. One adopts a broad interpretation of the consequences of an option and has great intuitive appeal. The other adopts a narrow interpretation of the consequences of an option and seems to have certain technical and practical advantages. I contend that the version of the rule that interprets consequences narrowly does indeed neglect attitudes toward risk. That version of the rule excludes the risk involved in an option from the consequences of the option and, contrary to what is usually claimed, cannot make up for this exclusion through adjustments in probability and utility assignments. I construct a new, general argument that establishes this in a rigorous way. On the other hand, I contend that the version of the rule that interprets consequences broadly takes account of attitudes toward risk by counting the risk involved in an option among the consequences of the option. I rebut some objections to this version of the rules, in particular, the objection that the rule lacks practical interest. Drawing upon the literature on 'mean-risk' decision rules, I show that this version of the rule can be used to solve some realistic decision problems.

How do rational agents coordinate in a single-stage, noncooperative game? Common knowledge of the payoff matrix and of each player's utility maximization among his strategies does not suffice. This paper argues that utility maximization among intentions and then acts generates coordination yielding a payoff-dominant Nash equilibrium. ‡I thank the audience at my paper's presentation at the 2006 PSA meeting for many insightful points. †To contact the author, please write to: Philosophy Department, University of Missouri, Columbia, MO 65211; e-mail: [email protected].

Decision theory aims at a general account of rationality covering humans but to begin makes idealizations about decision problems and agents' resources and circumstances. It treats inerrant agents with unlimited cognitive power facing tractable decision problems. This book systematically rolls back idealizations and without loss of precision treats errant agents with limited cognitive abilities facing decision problems without a stable top option. It recommends choices that maximize utility using quantizations of beliefs and desires in cases where probabilities and utilities are indeterminate and using higher-order utility analysis in cases of limited access to probabilities and utilities. For agents burdened with mistakes, it advocates reasonable attempts to correct unacceptable mistakes before deciding. In decision problems without a stable top option, a topic of game theory, it proposes maximizing self-conditional utility among self-supporting options. In games of strategy, the new principles lead to solutions that are Pareto optimal among equilibria composed of jointly self-supporting strategies. Offering an account of bounded rationality, the bookmakes large strides toward realism in decision theory.

Weirich examines three competing views entertained by economic theory about the instrumental rationality of decisions: the first says to maximize self-interest, the second to maximize utility, and the third to satisfice, that is, to adopt a satisfactory option. Critics argue that the first view is too narrow, that the second overlooks the benefits of teamwork and planning, and that the third, when carefully formulated, reduces to the second. Weirich defends a refined version of the principle to maximize utility. A broad conception of utility makes it responsive to the motives and benefits critics allege it overlooks. He discusses generalizations of utility theory to extend it to nonquantitative cases and other cases with nonstandard features.

Standard principles of rational decision assume that an option's utility is both comprehensive and accessible. These features constrain interpretations of an option's utility. This essay presents a way of understanding utility and laws of utility. It explains the relation between an option's utility and its outcome's utility and argues that an option's utility is relative to a specification of the option. Utility's relativity explains how a decision problem's framing affects an option's utility and its rationality even for an agent who is cognitively perfect and lacks only empirical information. The essay rewrites standard laws of utility to accommodate relativization to propositions' specifications. The new laws are generalizations of the standard laws and yield them as special cases.

This paper summarizes and rebuts the three standard objections made by social choice theorists against interpersonal utility. The first objection argues that interpersonal utility is measningless. I show that this objection either focuses on irrelevant kinds of meaning or else uses implausible criteria of meaningfulness. The second objection argues that interpersonal utility has no role to play in social choice theory. I show that on the contrary interpersonal utility is useful in formulating goals for social choice. The third objection argues that interpersonal utility in social choice theory can be replaced by clearer notions. I show that the replacements proposed are unsatisfactory in either interpersonal utility's descriptive or explanatory role. My conclusion is that interpersonal utility has a legitimate place in social choice theory.

Groups of people perform acts. For example, a committee passes a resolution, a team wins a game, and an orchestra performs a symphony. These collective acts may be evaluated for rationality. Take a committee’s passing a resolution. This act may be evaluated not only for fairness but also for rationality. Did it take account of all available information? Is the resolution consistent with the committee’s past resolutions? Standards of collective rationality apply to collective acts, that is, acts that groups of people perform. What makes a collective act evaluable for rationality? What methods of evaluation apply to collective acts? This paper addresses these two questions. Collective rationality is rationality’s extension from individuals to groups. The paper’s first few sections review key points about rationality. They identify the features of an individual’s act that make it evaluable for rationality and distinguish rationality’s methods of evaluating acts directly and indirectly controlled. This preliminary work yields general principles of rationality for all agents, both individuals and groups. Applying the general principles to groups answers the paper’s two main questions about collective rationality.

A computer simulation runs a model generating a phenomenon under investigation. For the simulation to be explanatory, the model has to be explanatory. The model must be isomorphic to the natural system that realizes the phenomenon. This paper elaborates the method of assessing a simulation's explanatory power. Then it illustrates the method by applying it to two simulations in game theory. The first is Brian Skyrms's (1990) simulation of interactive deliberations. It is intended to explain the emergence of a Nash equilibrium in a noncooperative game. The second is Skyrms's (2004) simulation of the evolution of cooperation. It is intended to explain cooperation in assurance games. The final section suggests ways of enhancing the explanatory power of these simulations.

To handle epistemic and pragmatic risks, Gärdenfors and Sahlin (1982, 1988) design a decision procedure for cases in which probabilities are indeterminate. Their procedure steps outside the traditional expected utility framework. Must it do this? Can the traditional framework handle risk? This paper argues that it can. The key is a comprehensive interpretation of an option's possible outcomes. Taking possible outcomes more broadly than Gärdenfors and Sahlin do, expected utility can give risk its due. In particular, Good's (1952) decision procedure adequately handles indeterminate probabilities and the risks they generate.

Theories of rationality advance principles that differ in topic, scope, and assumptions. A typical version of the principle of utility maximization formulates a standard rather than a procedure for decisions, evaluates decisions comprehensively, and relies on idealizations. I generalize the principle by removing some idealizations and making adjustments for their absence. The generalizations accommodate agents who have incomplete probability and utility assignments and are imperfectly rational. They also accommodate decision problems with unstable comparisons of options.

Abner Shimony argues that degrees of belief satisfy the axioms of probability because their epistemic goal is to match estimates of objective probabilities. Because the estimates obey the axioms of probability, degrees of belief must also obey them to reach their epistemic goal. This calibration argument meets some objections, but with a few revisions it can surmount those objections. It offers a good alternative to the Dutch book argument for compliance with the probability axioms. The defense of Shimony's calibration argument examines rational pursuit of an epistemic goal, introduces strength of evidence and its measurement, and distinguishes epistemic goals and functions.

Does rational bargaining yield a social contract that is efficient and so inclusive? A core allocation, that is, an allocation that gives each coalition at least as much as it can get on its own, is efficient. However, some coalitional games lack a core allocation, so rationality does not require one in those games. Does rationality therefore permit exclusion from the social contract? I replace realization of a core allocation with another type of equilibrium achievable in every coalitional game. Fully rational agents coordinate the pursuit of incentives so that equilibria of this type are efficient. They adopt a social contract that is efficient and inclusive

Food products with genetically modified ingredients are common, yet many consumers are unaware of this. When polled, consumers say that they want to know whether their food contains GM ingredients, just as many want to know whether their food is natural or organic. Informing consumers is a major motivation for labeling. But labeling need not be mandatory. Consumers who want GM-free products will pay a premium to support voluntary labeling. Why do consumers want to know about GM ingredients? GM foods are tested to ensure safety and have been on the market for more than a decade. Still, many consumers, including some with food allergies, want to be cautious. Also, GM crops may affect neighboring plants through pollen drift. Despite tests for environmental impact, some consumers may worry that GM crops will adversely effect the environment. The study of risk and its management raises questions not settled by the life sciences alone. This book surveys various labeling policies and the cases for them. It is the first comprehensive, interdisciplinary treatment of the debate about labeling genetically modified food. The contributors include philosophers, bioethicists, food and agricultural scientists, attorneys/legal scholars, and economists.

Agents face serious obstacles to making optimal decisions. For instance, their cognitive limits stand in the way. John Pollock’s book, Thinking about Acting , suggests many ways of revising decision principles to accommodate human limits and to direct limited, artificial agents. The book’s main proposal is to replace optimization, or expected-utility maximization, with locally global planning. This essay describes optimization and locally global planning, and then argues that optimization among salient options has the virtues of locally global planning without certain drawbacks. Although it does not endorse locally global planning, it recommends that decision theory incorporate some of the book’s ideas about settling for improvements when optimization among all options is unrealistic.