行为决策理论之父：纪念Edwards教授2周年忌辰

著名心理学家W ard Edwards对行为决策的学科形成与理论发展作出了巨大贡献。文章简要介绍了Edwards的生平,以主观期望效用模型和贝叶斯决策为核心回顾了Edwards的决策理论、主要成就及其对行为决策研究的学术贡献。文章并从行为决策领域的研究、科普、应用及人才培养等方面总结了中国行为决策研究的发展历程,以及Edwards的学术思想对中国行为决策研究的主要影响。文章展望了行为决策研究的前景,并呼吁更多的中国心理学工作者投身于行为决策研究。     

Bayesian probability

Bayesian decision theory is here construed as explicating a particular concept of rational choice and Bayesian probability is taken to be the concept of probability used in that theory. Bayesian probability is usually identified with the agent’s degrees of belief but that interpretation makes Bayesian decision theory a poor explication of the relevant concept of rational choice. A satisfactory conception of Bayesian decision theory is obtained by taking Bayesian probability to be an explicatum for inductive probability given the agent’s evidence.     

Partial Structures and Jeffrey-Keynes Algebras

In Tsuji 1997 the concept of Jeffrey-Keynes algebras was introduced in order to construct a paraconsistent theory of decision under uncertainty. In the present paper we show that these algebras can be used to develop a theory of decision under uncertainty that measures the degree of belief on the quasi (or partial) truth of the propositions. As applications of this new theory of decision, we use it to analyze Popper's paradox of ideal evidence and to indicate a possible way of formalizing Keynes' theory of economic action.     

Toward a unified theory of decision criterion learning in perceptual categorization

Optimal decision criterion placement maximizes expected reward and requires sensitivity to the category base rates (prior probabilities) and payoffs (costs and benefits of incorrect and correct responding). When base rates are unequal, human decision criterion is nearly optimal, but when payoffs are unequal, suboptimal decision criterion placement is observed, even when the optimal decision criterion is identical in both cases. A series of studies are reviewed that examine the generality of this finding, and a unified theory of decision criterion learning is described (Maddox & Dodd, 2001). The theory assumes that two critical mechanisms operate in decision criterion learning. One mechanism involves competition between reward and accuracy maximization: The observer attempts to maximize reward, as instructed, but also places some importance on accuracy maximization. The second mechanism involves a flat-maxima hypothesis that assumes that the observer's estimate of the reward-maximizing decision criterion is determined from the steepness of the objective reward function that relates expected reward to decision criterion placement. Experiments used to develop and test the theory require each observer to complete a large number of trials and to participate in all conditions of the experiment. This provides maximal control over the reinforcement history of the observer and allows a focus on individual behavioral profiles. The theory is applied to decision criterion learning problems that examine category discriminability, payoff matrix multiplication and addition effects, the optimal classifier's independence assumption, and different types of trial-by-trial feedback. In every case the theory provides a good account of the data, and, most important, provides useful insights into the psychological processes involved in decision criterion learning.     

Dynamic consistency in the logic of decision

Philosophical Studies - Arif Ahmed has recently argued that causal decision theory is dynamically inconsistent and that we should therefore prefer evidential decision theory. However, the principal...     

Modelling the Moral Dimension of Decisions

In this paper we explore the connections between ethics and decision theory. In particular, we consider the question of whether decision theory carries with it a bias towards consequentialist ethical theories. We argue that there are plausible versions of the other ethical theories that can be accommodated by “standard” decision theory, but there are also variations of these ethical theories that are less easily accommodated. So while “standard” decision theory is not exclusively consequentialist, it is not necessarily ethically neutral. Moreover, even if our decision‐theoretic models get the right answers vis‐à‐vis morally correct action, the question remains as to whether the motivation for the non‐consequentialist theories and the psychological processes of the agents who subscribe to those ethical theories are lost or poorly represented in the resulting models.     

Binding and its consequences

In “Bayesianism, Infinite Decisions, and Binding”, Arntzenius et al. (Mind 113:251–283, 2004) present cases in which agents who cannot bind themselves are driven by standard decision theory to choose sequences of actions with disastrous consequences. They defend standard decision theory by arguing that if a decision rule leads agents to disaster only when they cannot bind themselves, this should not be taken to be a mark against the decision rule. I show that this claim has surprising implications for a number of other debates in decision theory. I then assess the plausibility of this claim, and suggest that it should be rejected.     

Neural affective decision theory: Choices, brains, and emotions

We present a theory and neurocomputational model of how specific brain operations produce complex decision and preference phenomena, including those explored in prospect theory and decision affect theory. We propose that valuation and decision making are emotional processes, involving interacting brain areas that include two expectation-discrepancy subsystems: a dopamine-encoded system for positive events and a serotonin-encoded system for negative ones. The model provides a rigorous account of loss aversion and the shape of the value function from prospect theory. It also suggests multiple distinct neurological mechanisms by which information framing may affect choices, including ones involving anticipated pleasure. It further offers a neural basis for the interactions among affect, prior expectations and counterfactual comparisons explored in decision affect theory. Along with predicting the effects of particular brain disturbances and damage, the model suggests specific neurological explanations for individual differences observed in choice and valuation behaviors.     

Approval-directed agency and the decision theory of Newcomb-like problems

Decision theorists disagree about how instrumentally rational agents, i.e., agents trying to achieve some goal, should behave in so-called Newcomb-like problems, with the main contenders being causal and evidential decision theory. Since the main goal of artificial intelligence research is to create machines that make instrumentally rational decisions, the disagreement pertains to this field. In addition to the more philosophical question of what the right decision theory is, the goal of AI poses the question of how to implement any given decision theory in an AI. For example, how would one go about building an AI whose behavior matches evidential decision theory’s recommendations? Conversely, we can ask which decision theories (if any) describe the behavior of any existing AI design. In this paper, we study what decision theory an approval-directed agent, i.e., an agent whose goal it is to maximize the score it receives from an overseer, implements. If we assume that the overseer rewards the agent based on the expected value of some von Neumann–Morgenstern utility function, then such an approval-directed agent is guided by two decision theories: the one used by the agent to decide which action to choose in order to maximize the reward and the one used by the overseer to compute the expected utility of a chosen action. We show which of these two decision theories describes the agent’s behavior in which situations.

     

No Regrets, or: Edith Piaf Revamps Decision Theory

I argue that standard decision theories, namely causal decision theory and evidential decision theory, both are unsatisfactory. I devise a new decision theory, from which, under certain conditions, standard game theory can be derived.

Inferences from decision difficulty

We propose that people infer the relative attractiveness of the choice alternatives from decision difficulty. A difficult decision signifies that the alternatives are close to each other in attractiveness, and an easy decision signifies that the alternatives are remote from each other in attractiveness. In Study 1, observers used reported decision difficulty to infer preferences of the decision maker. Studies 2-4 showed that inferences about the source of one’s own decision difficulty may affect a decision maker’s preferences. Study 4 integrates the notion of inferences from decision difficulty with dissonance theory, showing that in repeatable decisions difficulty reduces post-decisional spreading of alternatives, as predicted by our model, whereas with one-time decisions, difficulty enhances post-decisional spreading of alternatives, as predicted by dissonance theory.     

A Note in Defence of Ratificationism

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.     

Do Politicians Take Risks Like the Rest of Us? An Experimental Test of Prospect Theory Under MPs

Political psychologists have been quick to use prospect theory in their work, realizing its potential for explaining decisions under risk. Applying prospect theory to political decision‐making is not without problems, though, and here we address two of these: (1) Does prospect theory actually apply to political decision‐makers, or are politicians unlike the rest of us? (2) Which dimension do politicians use as their reference point when there are multiple dimensions (e.g., votes and policy)? We address both problems in an experiment with a unique sample of Dutch members of parliament as participants. We use well‐known (incentivized) decision situations and newly developed hypothetical political decision‐making scenarios. Our results indicate that politicians’ deviate from expected utility theory in the direction predicted by prospect theory but that these deviations are somewhat smaller than those of other people. Votes appear to be a more important determinant of politicians’ reference point than is policy.     

Reflections on deliberative coherence

This paper treats two problem cases in decision theory, the Newcomb problem and Reed Richter's Button III. Although I argue that, contrary to Richter, the latter case does not constitute a genuine counterexample to a standard general proposition of (causal) decision theory, I agree with and undertake to amplify his solution to the decision problem in Button III. I then apply the conclusions and distinctions in the foregoing treatment of Button III to the Newcomb problem and argue that a familiar version of the dominance argument for taking both boxes runs afoul of plausible general constraints on rational agency. The underlying theme of the paper is that basic considerations of epistemic coherence play an important role in dealing with problem cases in decision theory.     

决策风格的理论发展及建构：基于信息加工视角

决策风格是人们在决策中表现出来的习惯性或独特的行为模式, 对决策、管理等领域均有重要影响。近年兴起的决策风格理论主要基于个体信息加工策略, 如基于双加工理论和基于后悔情绪的决策风格模型等。决策风格对个体决策的影响表现在决策策略与偏差、情绪和无意识加工等方面。该领域在诸如决策风格的主要理论、测量工具和理论检验等方面亦取得积极进展, 未来研究方向应注意基于双加工理论和进化心理学建构决策风格理论。     

The Feasibility OF Collectives' Actions

Orthodox decision theory gives no advice to agents who hold two goods to be incommensurate in value because such agents will have incomplete preferences. According to standard treatments, rationality requires complete preferences, so such agents are irrational. Experience shows, however, that incomplete preferences are ubiquitous in ordinary life. In this paper, we aim to do two things: (1) show that there is a good case for revising decision theory so as to allow it to apply non-vacuously to agents with incomplete preferences, and (2) to identify one substantive criterion that any such non-standard decision theory must obey. Our criterion, Competitiveness, is a weaker version of a dominance principle. Despite its modesty, Competitiveness is incompatible with prospectism, a recently developed decision theory for agents with incomplete preferences. We spend the final part of the paper showing why Competitiveness should be retained, and prospectism rejected.     

Prospect relativity: how choice options influence decision under risk

In many theories of decision under risk (e.g., expected utility theory, rank-dependent utility theory, and prospect theory), the utility of a prospect is independent of other options in the choice set. The experiments presented here show a large effect of the available options, suggesting instead that prospects are valued relative to one another. The judged certainty equivalent for a prospect is strongly influenced by the options available. Similarly, the selection of a preferred prospect is strongly influenced by the prospects available. Alternative theories of decision under risk (e.g., the stochastic difference model, multialternative decision field theory, and range frequency theory), where prospects are valued relative to one another, can provide an account of these context effects.