Procedurally Rational Volunteers

The mixed-strategy equilibrium applied to the volunteer's dilemma (Diekmann, 1985 Diekmann , A. ( 1985 ). Volunteer's dilemma . Journal of Conflict Resolution , 29 , 605 – 610 .[Crossref], [Web of Science ®] , [Google Scholar]) predicts that the probability that at least 1 bystander volunteers decreases, if the number of bystander increases. I argue that this prediction lacks empirical support and demonstrate that an alternative solution concept from the literature on bounded rationality, the procedurally rational equilibrium (Osborne &; Rubinstein, 1998 Osborne , M. J. &; Rubinstein , A. ( 1998 ). Games with procedurally rational players . American Economic Review , 88 , 834 – 847 .[Web of Science ®] , [Google Scholar]), yields alternative predictions. I supply some empirical evidence that the alternative solution concept fares better in explaining observed behavior in the volunteer's dilemma.     

基于实时公交信息的乘客乘车决策研究

实时交通信息的发布使乘客出行更具灵活性.调查乘客对实时公交系统的应用情况及功能需求,并提取乘客乘车决策规则.考虑乘客决策的"有限理性"特征构建决策模型:将乘车舒适性因素转换为时间成本,运用云模型建立定量时间到定性概念的映射;依据出行参考点确定出行方案的因素权重,建立期望效用函数;构建不同的出行场景,运用决策模型进行出行方案排序.结果表明:该模型能够更大限度地克服乘客理性限制对决策的影响,对多线路多因素方案下的乘客乘车行为做出决策,决策结果符合乘客决策规则,有助于为公交资源的规划与管理提供指导依据.     

Bounded rational expectations and the stability of interest rate policy

The New Keynesian model has recently been subject to two serious criticisms: the model cannot produce plausible inflation and output dynamics following a monetary shock, and the stability of its dynamics suffers from indeterminacy. The procedures that have been proposed to eliminate these two shortcomings fall into two categories: the introduction of some sort of backward price indexation into the standard model and/or other forms of stickiness (like sticky information); and the adoption of some form of policy rule that completely offsets the effects of forward looking dynamics in the optimization process. In this paper we do not eradicate forward looking behavior from the dynamics of the New Keynesian model, neither do we impose some form of backward price indexation. We assume that private economic agents have forward looking behavior and that they do try to optimize with all available information; the only novelty is that they are allowed to make small mistakes near the rational expectations equilibrium, in a fully deterministic setup. These “near rational” or “bounded rational” expectations show that the dynamics of the model with active interest rate rules is much richer than the simple problem of local indeterminacy as is usually found in the literature.     

Holomorphic vector fields with totally degenerate zeroes

A zero set of a holomorphic vector field is totally degenerate, if the endomorphism of the conormal sheaf induced by the vector field is identically zero. By studying a class of foliations generalizing foliations of C^*-actions, we show that if a projective manifold admits a holomorphic vector field with a smooth totally degenerate zero component,then the manifold is stably birational to that component of the zero set.When the vector field has an isolated totally degenerate zero, we prove that the manifold is rational. This is a special case of Carrell's conjecture.     

关于良定问题

本文应用有限理性模型M,对非线性问题的良定性进行了统一的研究,对最优化、多目标最优化、非合作博弈和广义博弈得到了一些新的良定性结果.     

Algorithms for Pareto optimal exchange with bounded exchange cycles

We consider exchange markets with single-unit endowments and demands where there is a bound on the size of the exchange cycles. The computational problem we study is that of computing a Pareto optimal and individually rational allocation. We present polynomial-time algorithms to compute a Pareto optimal and individually rational allocation when preferences are strict, the exchange bound is two, or when Pareto optimality is replaced with weak Pareto optimality.     

How much information do we need?

Modern technology is succeeding in delivering more information to people at ever faster rates. Under traditional views of rational decision making where individuals should evaluate and combine all available evidence, more information will yield better decisions. But our minds are designed to work in environments where information is often costly and difficult to obtain, leading us to use simple fast and frugal heuristics when making many decisions. These heuristics typically ignore most of the available information and rely on only a few important cues. Yet they make choices that are accurate in their appropriate application domains, achieving ecological rationality through their fit to particular information structures. This paper presents four classes of simple heuristics that use limited information—recognition-based heuristics, one-reason decision mechanisms, multiple-cue elimination strategies, and quick sequential search mechanisms—applied to environments from stock market investment to judging intentions of other organisms to choosing a mate. The findings that ecological rationality can be achieved with limited information are also used to indicate how our mind’s design, relying on decision mechanisms tuned to specific environments, should be taken into account in our technology’s design, creating environments that can enable better decisions.     

Symmetric social choices and collective rationality

A social choice function C defined on the m-element subsets of a set X for n voters assigns a non-empty subset C(A,R) of A to each pair (A,R) in which ¦A¦ = m,A X, and R is an n-tuple of voter preference orders on X. When n > 2, 3 m < ¦X¦, and C satisfies natural conditions of independence, symmetry among voters and alternatives, and collective rationality, it is proved that C is completely indecisive in the sense that C(A,R) = A for all (A,R). This non-binary result complements a binary (m = 2) result proved by Hanson. It suggests that there is a fundamental incompatibility between collective rationality and conditions designed to assure equitable treatment of voters and of alternatives.     

Fuzzy adaptive decision-making for boundedly rational traders in speculative stock markets

The development of new models that would enhance predictability for time series with dynamic time-varying, nonlinear features is a major challenge for speculators. Boundedly rational investors called “chartists” use advanced heuristics and rules-of-thumb to make profit by trading, or even hedge against potential market risks. This paper introduces a hybrid neurofuzzy system for decision-making and trading under uncertainty. The efficiency of a technical trading strategy based on the neurofuzzy model is investigated, in order to predict the direction of the market for 10 of the most prominent stock indices of U.S.A, Europe and Southeast Asia. It is demonstrated via an extensive empirical analysis that the neurofuzzy model allows technical analysts to earn significantly higher returns by providing valid information for a potential turning point on the next trading day. The total profit of the proposed neurofuzzy model, including transaction costs, is consistently superior to a recurrent neural network and a Buy & Hold strategy for all indices, particularly for the highly speculative, emerging Southeast Asian markets. Optimal prediction is based on the dynamic update and adaptive calibration of the heuristic fuzzy learning rules, which reflect the psychological and behavioral patterns of the traders.