A standard way to challenge convergence-based accounts of inductive success is to claim that they are too weak to constrain inductive inferences in the short run. We respond to such a challenge by answering some questions raised by Juhl (1994). When it comes to predicting limiting relative frequencies in the framework of Reichenbach, we show that speed-optimal convergence—a long-run success condition—induces dynamic coherence in the short run.

A speaker wishes to persuade a listener to accept a certain request. The conditions under which the request is justified, from the listener’s point of view, depend on the values of two aspects. The values of the aspects are known only to the speaker and the listener can check the value of at most one. A mechanism specifies a set of messages that the speaker can send and a rule that determines the listener’s response, namely, which aspect he checks (...) and whether he accepts or rejects the speaker’s request. We study mechanisms that maximize the probability that the listener accepts the request when it is justified and rejects the request when it is unjustified, given that the speaker maximizes the probability that his request is accepted. We show that a simple optimal mechanism exists and can be found by solving a linear programming problem in which the set of constraints is derived from what we call the L-principle. (shrink)

This paper reports completeness results for dyadic deontic logics in the tradition of Hansson’s systems. There are two ways to understand the core notion of best antecedent-worlds, which underpins such systems. One is in terms of maximality, and the other in terms of optimality. Depending on the choice being made, one gets different evaluation rules for the deontic modalities, but also different versions of the so-called limit assumption. Four of them are disentangled, and compared. The main observation of this paper (...) is that, even in the partial order case, the contrast between maximality and optimality is not as significant as one could expect, because the logic remains the same whatever notion of best is used. This is established by showing that, given analogous properties for the betterness relation, the same system is sound and complete with respect to its intended modelling. The chief result of this paper concerns Åqvist’s system F supplemented with the principle of cautious monotony. It is established that, under the maximality rule, F + is sound and complete with respect to the class of models in which the betterness relation is required be reflexive and smooth . From this, a number of spin-off results are obtained. First and foremost, it is shown that a similar determination result holds for optimality; that is, under the optimality rule, F + is also sound and complete with respect to the class of models in which the betterness relation is reflexive and smooth . Other spin-off results concern classes of models in which further constraints are placed on the betterness relation, like totalness and transitivity. (shrink)

Despite several research on HIV/aids, it is still incumbent to investigate more effective control measures to mitigate its infection level. Therefore, we introduce an HIV/aids-resistant model with behavior change and study its basic properties. In order to determine the most sensitive parameters that are responsible for disease transmission with respect to the basic reproduction number and those responsible for disease prevalence with respect to the endemic equilibrium, the sensitivity analysis was established and it was confirmed that the influx rate of (...) people into the infected population and total abstinence from all risk practices and endemic areas are some of the most sensitive parameters for disease spread and disease eradication, respectively. Furthermore, by considering controls u1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$u_1$$\end{document} denoting the government’s intervention in promoting and encouraging behavior change, u2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$u_2$$\end{document} representing intake of balanced nutritional supplementation, and u3\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$u_3$$\end{document} connoting antiretroviral therapy (ART), an optimal control problem was developed and analyzed. Before the establishment of the necessary conditions of the optimal control using Pontryagin’s Maximum Principle, we proved the existence of the optimal control triplet (u1(t),u2(t),u3(t)∈Φ,\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(u_1(t),u_2(t),u_3(t)\in \Phi,$$\end{document} where Φ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Phi$$\end{document} is the control set at time t,) which has been neglected by many researchers in recent years. Using the Runge–Kutta scheme, the optimal control problem was solved to understand the best combination of control strategies. Using the demographic and epidemiological data for South Africa on HIV/aids, a numerical simulation was carried out and results are presented on 3D surface plots. The obtained results suggested that the combination of all the considered control measures is the best method to ensure disease eradication. (shrink)

Conditional automated driving [level 3, Society of Automotive Engineers ] requires drivers to take over the vehicle when an automated system’s failure occurs or is about to leave its operational design domain. Two-stage warning systems, which warn drivers in two steps, can be a promising method to guide drivers in preparing for the takeover. However, the proper time intervals of two-stage warning systems that allow drivers with different personalities to prepare for the takeover remain unclear. This study explored the (...) class='Hi'>optimal time intervals of two-stage warning systems with insights into the drivers’ neuroticism personality. A total of 32 drivers were distributed into two groups according to their self-ratings in neuroticism. Each driver experienced takeover under the two-stage warning systems with four time intervals. The takeover performance and subjective opinions for time intervals and situation awareness were recorded. The results showed that drivers in the 5-s time interval had the best takeover preparation. Furthermore, both the 5- and 7-s time intervals resulted in more rapid takeover reactions and were rated more appropriate and useful than the 3- and 9-s time intervals. In terms of personality, drivers with high neuroticism tended to take over immediately after receiving takeover messages, at the cost of SA deficiency. In contrast, drivers with low neuroticism responded safely by judging whether they gained enough SA. We concluded that the 5-s time interval was optimal for drivers in two-stage takeover warning systems. When considering personality, drivers with low neuroticism had no strict requirements for time intervals. However, the extended time intervals were favorable for drivers with high neuroticism in developing SA. The present findings have reference implications for designers and engineers to set the time intervals of two-stage warning systems according to the neuroticism personality of drivers. (shrink)

Focus of attention is one of the most influential factors facilitating motor performance. Previous evidence supports that the external focus strategy, which directs attention to movement outcomes, is associated with better motor performance than the internal focus strategy, which directs attention to body movements. However, recent studies have reported that the EF strategy is not effective for some individuals. Furthermore, neuroimaging studies have demonstrated that the frontal and parietal areas characterize individual optimal attentional strategies for motor tasks. However, whether (...) the sensory cortices are also functionally related to individual optimal attentional strategy remains unclear. Therefore, the present study examined whether an individual’s sensory processing ability would reflect the optimal attentional strategy. To address this point, we explored the relationship between responses in the early sensory cortex and individuals’ optimal attentional strategy by recording steady-state somatosensory evoked potentials and steady-state visual evoked potentials. Twenty-six healthy young participants first performed a motor learning task with reaching movements under IF and EF conditions. Of the total sample, 12 individuals showed higher after-effects under the IF condition than the EF condition, whereas the remaining individuals showed the opposite trend. Subsequently, we measured SSSEP from bilateral primary somatosensory cortices while presenting vibrotactile stimuli and measured SSVEP from bilateral primary visual cortices while presenting checkerboard visual stimuli. The degree of increasing SSSEP response when the individuals in the IF-dominant group directed attention to vibrotactile stimuli was significantly more potent than those in the EF-dominant individuals. By contrast, the individuals in the EF-dominant group showed a significantly larger SSVEP increase while they directed attention to visual stimuli compared with the IF-dominant individuals. Furthermore, a significant correlation was observed such that individuals with more robust IF dominance showed more pronounced SSSEP attention modulation. These results suggest that the early sensory areas have crucial brain dynamics to characterize an individual’s optimal attentional strategy during motor tasks. The response characteristics may reflect the individual sensory processing ability, such as control of priority to the sensory inputs. Considering individual cognitive traits based on the suitable attentional strategy could enhance adaptability in motor tasks. (shrink)

A long-standing problem in biology, economics, and social sciences is to understand the conditions required for the emergence and maintenance of cooperation in evolving populations. This paper investigates how to promote the evolution of cooperation in the Prisoner’s Dilemma game. Differing from previous approaches, we not only propose a tag-based control mechanism but also look at how the evolution of cooperation by TBC can be successfully promoted. The effect of TBC on the evolutionary process of cooperation shows that it (...) can both reduce the payoff of defectors and inhibit defection; although when the cooperation rate is high, TBC will also reduce the payoff of cooperators unless the identified rate of the TBC is large enough. An optimal timing control of switched replicator dynamics is designed to consider the control costs, the cooperation rate at terminal time, and the cooperator’s payoff. The results show that the switching control between an optimal identified rate control of the TBC and no TBC can properly not only maintain a high cooperation rate but also greatly enhance the payoff of the cooperators. Our results provide valuable insights for some clusters, for example, logistics parks and government, to regard the decision to promote cooperation. (shrink)

As a promising method with excellent characteristics in terms of resilience and dependability, distributed methods are gradually used in the field of energy management of microgrid. However, these methods have more stringent requirements on the working conditions, which will make the system more sensitive to communication failures and cyberattacks. As a result, it is both theoretical merits and practical values to investigate the malicious effect of cyber attacks on microgrid. This paper studies the distributed economic dispatch problem under denial-of-service (...) attacks for the microgrid, in which each generator can communicate with its neighbors and has the computational capability to implement local operation. Firstly, a DoS attack model is proposed, in which the DoS attacker intentionally jams the communication channel to deteriorate the performance of the microgrid. Then, the evolution mechanism of the dispatch system of the microgrid under different attack scenarios is adequately discussed. On this basis, an optimal attack strategy based on enumerating-search algorithm is presented to allocate the limited attack resources reasonably, so as to maximize the effect of DoS attacks. Finally, the validity of the theoretical studies about the attack effect under different scenarios and the effectiveness of the proposed enumerating-search-based optimal attack strategy are illustrated through the simulation examples on the IEEE 57-bus system and IEEE 39-bus system, respectively. (shrink)

In causal inference, a variety of causal effect estimands have been studied, including the sample, uncensored, target, conditional, optimal subpopulation, and optimal weighted average treatment effects. Ad hoc methods have been developed for each estimand based on inverse probability weighting and on outcome regression modeling, but these may be sensitive to model misspecification, practical violations of positivity, or both. The contribution of this article is twofold. First, we formulate the generalized average treatment effect to unify these causal estimands (...) as well as their IPW estimates. Second, we develop a method based on Kernel optimal matching to optimally estimate GATE and to find the GATE most easily estimable by KOM, which we term the Kernel optimal weighted average treatment effect. KOM provides uniform control on the conditional mean squared error of a weighted estimator over a class of models while simultaneously controlling for precision. We study its theoretical properties and evaluate its comparative performance in a simulation study. We illustrate the use of KOM for GATE estimation in two case studies: comparing spine surgical interventions and studying the effect of peer support on people living with HIV. (shrink)

Making proper decisions in today’s complex world is a challenging task for decision makers. A promising approach that can support decision makers to have a better understanding of complex systems is agent-based modeling. ABM has been developing during the last few decades as a methodology with many different applications and has enabled a better description of the dynamics of complex systems. However, the prescriptive facet of these applications is rarely portrayed. Adding a prescriptive decision-making aspect to ABM can support the (...) decision makers in making better or, in some cases, optimized decisions for the complex problems as well as explaining the investigated phenomena. In this paper, first, the literature of DM with ABM is inquired and classified based on the methods of integration. Performing a scientometric analysis on the relevant literature lets us conclude that the number of publications attempting to integrate DM and ABM has not grown during the last two decades, while analysis of the current methodologies for integrating DM and ABM indicates that they have serious drawbacks. In this regard, a novel nature-inspired model articulation called optimal agent framework has been proposed to ameliorate the disadvantages and enhance the realization of proper decisions in ABM at a relatively low computational cost. The framework is examined with the Bass diffusion model. The results of the simulation for the customized model developed by OAF have verified the feasibility of the framework. Moreover, sensitivity analyses on different agent populations, network structures, and marketing strategies have depicted the great potential of OAF to find the optimal strategies in various stochastic and unconventional conditions which have not been addressed prior to the implementation of the framework. (shrink)

To be optimistic, it is standardly assumed, is to have positive expectations. I here argue that this definition is correct but captures only one variety of optimism – here called factual optimism. It leaves out two other important varieties of optimism. The first – focal optimism – corresponds to the idea of seeing the glass half full. The second – axiological optimism – consists in the view that good is stronger than bad. Those three varieties of optimism are irreducible to (...) each other and do not belong to a common kind. I define each of these, characterize their respective correctness conditions, and contrast hope with optimism. (shrink)

The purpose of the paper is to use analytical method and optimization tool to suggest a vaccination program intensity for a basic SIR epidemic model with limited resources for vaccination. We show that there are two different scenarios for optimal vaccination strategies, and obtain analytical solutions for the optimal control problem that minimizes the total cost of disease under the assumption of daily vaccine supply being limited. These solutions and their corresponding optimal control policies are derived explicitly (...) in terms of initial conditions, model parameters and resources for vaccination. With sufficient resources, the optimal control strategy is the normal Bang–Bang control. However, with limited resources, the optimal control strategy requires to switch to time-variant vaccination. (shrink)

We study a dynamic game in which players can steal parts of a homogeneous and perfectly divisible pie from each other. The effectiveness of a player’s theft is a random function which is stochastically increasing in the share of the pie the agent currently owns. We show how the incentives to preempt or to follow the rivals change with the number of players involved in the game and investigate the conditions that lead to the occurrence of symmetric or asymmetric (...) equilibria. (shrink)

In this book, we present a study of linear models and algorithms to find the optimal solution for them using the concepts of neuroscientific science. We know that the linear programming method is one of the important methods of operations research, the science that was the product of the great scientific development that our contemporary world is witnessing. The name operations research is given to the group of scientific methods used. In analyzing problems and searching for optimal solutions, (...) it is a science whose applications have achieved widespread success in various fields of life. What is meant by neutrosophic models are models in which the data are neutrosophic values, that is, variables such as in the objective function, which expresses profit if the model is a maximization model, and expresses a cost if the model is a minimization model, which in turn is affected by environmental conditions. (shrink)

A necessary condition for a group being taken as a rational agent is that its choices and judgements are ‘logically contestable’, but this can lead to problems of aggregation, as Arrow impossibility theorem or the discursive dilemma. This paper proposes a contractarian or constitutional approach: the relevant thing is what aggregation mechanisms would be preferred by the members of the group. Two distinctions need to be made: first, judgement aggregation is not aggregation of decisions, and judgement aggregation needs be distinguished (...) from the aggregation of information: we assume that every member of the group has already taken into account the opinions of the other members, by means of a process of public deliberation, but they may end having different opinions; we also assume that the members are rational, so that they have no reasons to accept further changes in their individual opinions. So, from the epistemic point of view, the collective judgment is not a 'better' opinion than those of the individual members. The collective judgement is better seen as a kind of compromise, the outcome of a ‘bargain’, so to say. Basically, we assume that individuals will have an interest in choosing a specific aggregation function by taking into account how are they affected by the collective actions carried out by the group, and grounded on the chosen collective judgement. (shrink)

The notion of optimality is often invoked informally in the literature on metacognitive control. We provide a precise formulation of the optimization problem and show that optimal time allocation strategies depend critically on certain characteristics of the learning environment, such as the extent of time pressure, and the nature of the uptake function. When the learning curve is concave, optimality requires that items at lower levels of initial competence be allocated greater time. On the other hand, with logistic learning (...) curves, optimal allocations vary with time availability in complex and surprising ways. Hence there are conditions under which optimal strategies will be relatively easy to uncover, and others in which suboptimal time allocation might be expected. The model can therefore be used to address the question of whether and when learners should be able to exercise good metacognitive control in practice. (shrink)

The motivation of someone who is locked-in, that is, paralyzed and mute, is to find relief for their loss of function. The data presented in this report is part of an attempt to restore one of those lost functions, namely, speech. An essential feature of the development of a speech prosthesis is optimal decoding of patterns of recorded neural signals during silent or covert speech, that is, speaking “inside the head” with output that is inaudible due to the paralysis (...) of the articulators. The aim of this paper is to illustrate the importance of both fast and slow single unit firings recorded from an individual with locked-in syndrome and from an intact participant speaking silently. Long duration electrodes were implanted in the motor speech cortex for up to 13 years in the locked-in participant. The data herein provide evidence that slow firing single units are essential for optimal decoding accuracy. Additional evidence indicates that slow firing single units can be conditioned in the locked-in participant 5 years after implantation, further supporting their role in decoding. (shrink)

When visual attention is directed away from a stimulus, neural processing is weak and strength and precision of sensory data decreases. From a computational perspective, in such situations observers should give more weight to prior expectations in order to behave optimally during a discrimination task. Here we test a signal detection theoretic model that counter-intuitively predicts subjects will do just the opposite in a discrimination task with two stimuli, one attended and one unattended: when subjects are probed to discriminate the (...) unattended stimulus, they rely less on prior information about the probed stimulus’ identity. The model is in part inspired by recent findings that attention reduces trial-by-trial variability of the neuronal population response and that they use a common criterion for attended and unattended trials. In five different visual discrimination experiments, when attention was directed away from the target stimulus, subjects did not adjust their response bias in reaction to a change in stimulus presentation frequency despite being fully informed and despite the presence of performance feedback and monetary and social incentives. This indicates that subjects did not rely more on the priors under conditions of inattention as would be predicted by a Bayes-optimal observer model. These results inform and constrain future models of Bayesian inference in the human brain. (shrink)

This paper discusses problems associated with the use of optimality models in human behavioral ecology. Optimality models are used in both human and non-human animal behavioral ecology to test hypotheses about the conditions generating and maintaining behavioral strategies in populations via natural selection. The way optimality models are currently used in behavioral ecology faces significant problems, which are exacerbated by employing the so-called ‘phenotypic gambit’: that is, the bet that the psychological and inheritance mechanisms responsible for behavioral strategies will (...) be straightforward. I argue that each of several different possible ways we might interpret how optimality models are being used for humans face similar and additional problems. I suggest some ways in which human behavioral ecologists might adjust how they employ optimality models; in particular, I urge the abandonment of the phenotypic gambit in the human case. (shrink)

This note examines the theory of optimal insurance purchasing in the presence of a nonpecuniary background risk. The occurrence of the qualitative uninsurable background loss can increase, decrease or can leave the marginal utility of wealth unchanged, whereas a financial background loss (as in Doherty and Schlesinger, 1883a) always increases it. Existing theorems on the optimal level of insurance and the optimal form of insurance contracts are shown to hold only under restrictive assumptions on the correlation level (...) between risks. The paper shows that sufficient conditions for the validity of the theorems depend not only on the correlation between the insurable and noninsurable losses, but also on the variation of the marginal utility of wealth with respect to the nonpecuniary variable. (shrink)

Hans Reichenbach made a bold and original attempt to ‘vindicate’ induction. He proposed a rule, the ‘straight rule’ of induction, which would guarantee inductive success if any rule of induction would. A central problem facing his attempt to vindicate the straight rule is that too many other rules are just as good as the straight rule if our only constraint on what counts as ‘success’ for an inductive rule is that it is ‘asymptotic’, i.e. that it converges in the limit (...) to the true limiting frequency (of some type of outcome O in a sequence of events) whenever such a limiting frequency exists. In this paper I consider the consequences of requiring speed-optimality of asymptotic methods, that is, requiring that inductive methods must get to the truth as quickly as possible. Two main results are proved: (1) the straight rule is speed-optimal; (2) there are (uncountably) many non-speed-optimal asymptotic methods. A further result gives a sufficient but not necessary condition for speed-optimality among asymptotic methods. Some consequences and open questions are then discussed. (shrink)

It has been reported as a robust effect that people are likely to select a matching case in the Wason selection task. For example, they usually select the 5 case, in the Wason selection task with the conditional "if an E, then a not-5". This was explained by the matching bias account that people are likely to regard a matching case as relevant to the truth of the conditional (Evans, 1998). However, because a positive concept usually constructs a smaller set (...) than its negative one does (a rarity assumption), it is more effective to get information on the truth of the conditional in a positive set than in a negative set. Thus the optimal data selection account can also explain the effect. The set size of Q and matching by introducing negation were manipulated independently in four experiments. From the results it was inferred that the so-called matching bias was an amalgam of two different cognitive components-relevance judgement by matching and optimal data selection. (shrink)

In this paper, we derive necessary and sufficient conditions on team based tasks in order for a selection criterion applied to individuals to produce optimal teams. We assume only that individuals have types and that a team’s performance depends on its size and the type composition of its members. We first derive the selection principle which states that if a selection criterion exists, it must rank types by homogeneous team performance, the performance of a team consisting only of (...) that type. We then prove that a selection criterion exists if and only if replacing the team’s lowest ranked type, as measured by homogeneous team performance, with a higher ranked type increases team performance. Finally, we show that the replace the lowest ranked property rules out most common types of team complementarities, including benefits to diverse types and types that fill structural holes. (shrink)

Humans display more conditioned fear when the conditioned stimulus in a fear conditioning paradigm is a picture of an individual from another race than when it is a picture of an individual from their own race (Olsson, Ebert, Banaji, & Phelps, 2005). These results have been interpreted in terms of a genetic “preparedness” to learn to fear individuals from different social groups (Ohman, 2005; Olsson et al., 2005). However, the associability of conditioned stimuli is strongly influenced by prior exposure to (...) those or similar stimuli. Using the Kalman filter, a normative statistical model, this article shows that superior fear conditioning to individuals from other groups is precisely what one would expect if participants perform optimal, Bayesian inference that takes their prior exposures to the different groups into account. There is therefore no need to postulate a genetic preparedness to learn to fear individuals from other races or social groups. (shrink)

An efficient intelligent fault diagnosis model was proposed in this paper to timely and accurately offer a dependable basis for identifying the rolling bearing condition in the actual production application. The model is mainly based on an improved butterfly optimizer algorithm- optimized kernel extreme learning machine model. Firstly, the roller bearing’s vibration signals in the four states that contain normal state, outer race failure, inner race failure, and rolling ball failure are decomposed into several intrinsic mode functions using the complete (...) ensemble empirical mode decomposition based on adaptive noise. Then, the amplitude energy entropies of IMFs are designated as the features of the rolling bearing. In order to eliminate redundant features, a random forest was used to receive the contributions of features to the accuracy of results, and subsets of features were set up by removing one feature in the descending order, using the classification accuracy of the SBOA-KELM model as the criterion to obtain the optimal feature subset. The salp swarm algorithm was introduced to BOA to improve optimization ability, obtain optimal KELM parameters, and avoid the BOA deteriorating into local optimization. Finally, an optimal SBOA-KELM model was constructed for the identification of rolling bearings. In the experiment, SBOA was validated against ten other competitive optimization algorithms on 30 IEEE CEC2017 benchmark functions. The experimental results validated that the SBOA was evident over existing algorithms for most function problems. SBOA-KELM employed for diagnosing the fault diagnosis of rolling bearings obtained improved classification performance and higher stability. Therefore, the proposed SBOA-KELM model can be effectively used to diagnose faults of rolling bearings. (shrink)

This paper reports on an experimental test of the Principle of Optimality in dynamic decision problems. This Principle, which states that the decision-maker should always choose the optimal decision at each stage of the decision problem, conditional on behaving optimally thereafter, underlies many theories of optimal dynamic decision making, but is normally difficult to test empirically without knowledge of the decision-maker's preference function. In the experiment reported here we use a new experimental procedure to get round this difficulty, (...) which also enables us to shed some light on the decision process that the decision-maker is using if he or she is not using the Principle of Optimality - which appears to be the case in our experiments. (shrink)

In this paper, we discuss some formal properties of the model ofbidirectional Optimality Theory that was developed inBlutner (2000). We investigate the conditions under whichbidirectional optimization is a well-defined notion, and we give aconceptually simpler reformulation of Blutner's definition. In thesecond part of the paper, we show that bidirectional optimization can bemodeled by means of finite state techniques. There we rely heavily onthe related work of Frank and Satta (1998) about unidirectionaloptimization.

An expected utility model of individual choice is formulated which allows the decision maker to specify his available actions in the form of controls (partial contingency plans) and to simultaneously choose goals and controls in end-mean pairs. It is shown that the Savage expected utility model, the Marschak- Radner team model, the Bayesian statistical decision model, and the standard optimal control model can be viewed as special cases of this goal-control expected utility model.

Given free information and unlimited processing power, should decision algorithms use as much information as possible? A formal model of the decision-making environment is developed to address this question and provide conditions under which informationally frugal algorithms, without any information or processing costs whatsoever, are optimal. One cause of compression that allows optimal algorithms to rationally ignore information is inverse movement of payoffs and probabilities (e.g., high payoffs occur with low probably and low payoffs occur with high (...) probability). If inversely related payoffs and probabilities cancel out, then predictors that correlate with payoffs and consequently condition the probabilities associated with different payoffs will drop out of the expected-payoff objective function, severing the link between information and optimal action rules. Stochastic payoff processes in which rational ignoring occurs are referred to as compressed environments, because optimal action depends on a reduced-dimension subset of the environmental parameters. This paper considers benefits and limitations of economic models versus other methods for studying links between environmental structure and the real-world success of simple decision procedures. Different methods converge on the normative proposition of ecological rationality, as opposed to axiomatic rationality based on informational efficiency and internal consistency axioms, as a superior framework for comparing the effectiveness of decision strategies and prescribing decision algorithms in application. (shrink)

Jerry Fodor has proposed a causal theory of meaning based on the notion of a certain asymmetric dependency between the causes of a symbol's tokens. This theory is held to be an improvement on Dennis Stampe's causal theory of meaning and Fred Dretske's information theoretic account, because it allegedly solves what Fodor calls the “disjunction problem”, and does so without recourse to the kind of optimal (ideal) conditions to which Stampe and Dretske appeal. A series of counterexamples is (...) proposed to Fodor's account, which, it is argued, can only be met by reintroducing that same appeal to optimal conditions that he had sought to eliminate. It is then argued that Fodor's notion of asymmetric dependence is not fundamental to the explanation of why a symbol means what it does: on the contrary, the symbol's meaning what it does is explanatorily prior to the obtaining of the asymmetry, so the asymmetry cannot be used to explain the symbol's meaning. Finally, it is argued that the “disjunction problem “ as it is defined by Fodor is not a genuine problem for causal theories of meaning. (shrink)

Scoring rules measure the deviation between a forecast, which assigns degrees of confidence to various events, and reality. Strictly proper scoring rules have the property that for any forecast, the mathematical expectation of the score of a forecast p by the lights of p is strictly better than the mathematical expectation of any other forecast q by the lights of p. Forecasts need not satisfy the axioms of the probability calculus, but Predd et al. [9] have shown that given a (...) finite sample space and any strictly proper additive and continuous scoring rule, the score for any forecast that does not satisfy the axioms of probability is strictly dominated by the score for some probabilistically consistent forecast. Recently, this result has been extended to non-additive continuous scoring rules. In this paper, a condition weaker than continuity is given that suffices for the result, and the condition is proved to be optimal. (shrink)

The linear programming method is one of the important methods of operations research that has been used to address many practical issues and provided optimal solutions for many institutions and companies, which helped decision makers make ideal decisions through which companies and institutions achieved maximum profit, but these solutions remain ideal and appropriate in If the conditions surrounding the work environment are stable, because any change in the data provided will affect the optimal solution and to avoid (...) losses and achieve maximum profit, we have, in previous research, reformulated the linear models using the concepts of neutrosophic science, the science that takes into account the instability of conditions and fluctuations in the work environment and leaves nothing to chance. While taking data, neutrosophic values carry some indeterminacy, giving a margin of freedom to decision makers. In another research, we reformulated one of the most important methods used to solve linear models, which is the simplex method, using the concepts of this science, and as a continuation of what we did in the previous two researches, we will reformulate in this research. The graphical method for solving linear models using the concepts of neutrosophics. We will also shed light on a case that is rarely mentioned in most operations research references, which is that when the difference between the number of unknowns and the number of constraints is equal to one, two, or three, we can also find the optimal solution graphically for some linear models. This is done by taking advantage of the conditions of non-negativity that linear models have, and we will explain this through an example in which the difference is equal to two. Also, through examples, we will explain the difference between using classical values and neutrosophic values and the extent of this’s impact on the optimal solution. (shrink)

This paper shows that, if the performance of the economy is independent of the identities of individuals, then many welfare criteria yield sets of optimal social states that are equal to the Pareto optimal set. This result is proved for income distributions and extended to more general social choice problems. If the independence condition holds, then the set of optimal states is invariant to the adoption of an anonymity axiom, and to the utility information available.

Humans excel in categorization. Yet from a computational standpoint, learning a novel probabilistic classification task involves severe computational challenges. The present paper investigates one way to address these challenges: assuming class-conditional independence of features. This feature independence assumption simplifies the inference problem, allows for informed inferences about novel feature combinations, and performs robustly across different statistical environments. We designed a new Bayesian classification learning model that incorporates varying degrees of prior belief in class-conditional independence, learns whether or not independence holds, (...) and adapts its behavior accordingly. Theoretical results from two simulation studies demonstrate that classification behavior can appear to start simple, yet adapt effectively to unexpected task structures. Two experiments—designed using optimal experimental design principles—were conducted with human learners. Classification decisions of the majority of participants were best accounted for by a version of the model with very high initial prior belief in class-conditional independence, before adapting to the true environmental structure. Class-conditional independence may be a strong and useful default assumption in category learning tasks. (shrink)

Oaksford and Chater (1994) proposed to analyse the Wason selection task as an inductive instead of a deductive task. Applying Bayesian statistics, they concluded that the cards that participants tend to select are those with the highest expected information gain. Therefore, their choices seem rational from the perspective of optimal data selection. We tested a central prediction from the theory in three experiments: card selection frequencies should be sensitive to the subjective probability of occurrence for individual cards. In Experiment (...) 1, expected frequencies of the p- and the q-card were manipulated independently by concepts referring to large vs. small sets. Although the manipulation had an effect on card selection frequencies, there was only a weak correlation between the predicted and the observed patterns. In the second experiment, relative frequencies of individual cards were manipulated more directly by explicit frequency information. In addition, participants estimated probabilities for the four logical cases and of the conditional statement itself. The experimental manipulations strongly affected the probability estimates, but were completely unrelated to card selections. This result was replicated in a third experiment. We conclude that our data provide little support for optimal data selection theory. (shrink)

The phenomenon known as matching bias consists of a tendency to see cases as relevant in logical reasoning tasks when the lexical content of a case matches that of a propositional rule, normally a conditional, which applies to that case. Matching is demonstrated by use of the negations paradigm that is by using conditionals in which the presence and absence of negative components is systematically varied. The phenomenon was first published in 1972 and the present paper reviews the history of (...) research and theorising on the problem in the subsequent 25 years. Theories of matching bias considered include those based on several broad frameworks including the heuristic-analytic theory, the mental models theory, the theory of optimal data selection, and relevance theory as well as the specific processing-negations account. The ability of these theories to account for a range of phenomena is considered, including the effects of linguistic form, realistic content, and explicit negation on the matching bias effect. Of particular importance are recent findings showing that the bias is observable on a wider range of linguistic forms than has generally been thought, and that it is almost entirely dependent on the use of implicit negation in the logical cases to which rules are applied. The reasons for the general suppression of matching when realistic content is used are, however, unclear and a need for further research is identified here. It is concluded that matching bias is a highly robust effect which is closely connected with the problem of understanding implicit negation. Most of the theories in the literature are unable to account for at least some of the major phenomena discovered in research on the bias. The accounts that fare best are those that posit local effects of negation, including the heuristic-analytic and processing negations theories. (shrink)

This article focuses on the problem of criminal liability for unlawful engagement in economic activities, analyses the emergence and development of this norm in criminal law and the ways of its optimal explanation. Special attention is paid to the problem of identification of illegality of activities, based on specific tax and economic regulation. The study concludes that criminal liability must be limited to a violation of fundamental requirements for the legality of business, and does not include particular abuses occurring (...) in legal business. The author also deals with the criteria of delimitation of criminal and administrative liability for unlawful engagement in economic activities. Under Article 202(1) of the Criminal Code of the Republic of Lithuania, application of criminal liability is limited by two alternative conditions: either a person illegally undertakes activity in entrepreneurial way or on a large scale. According to the paper, the above-mentioned regulation lacks clarity and leads to the risk of unfounded prosecutions. The author gives practical examples, where on the basis of inexplicable criterion of an entrepreneurial way, criminal charges are filed in respect of petty economic activities. Such practice is incompatible with the purposes and principles of criminal law. The paper proposes to delete the criterion of an entrepreneurial way from the definition, leaving the possibility of criminal liability only in case of large scale illegal economic activity. The article also substantiates the conclusion that prohibited business activities provided for in Article 202(2) of the Criminal Code actually defies logical explanation and should be removed from the regulation. At the end of the article, the author offers a sample of optimal legal wording of unlawful engagement in economic activities in criminal law. (shrink)

This paper reports on an experimental test of the Principle of Optimality in dynamic decision problems. This Principle, which states that the decision-maker should always choose the optimal decision at each stage of the decision problem, conditional on behaving optimally thereafter, underlies many theories of optimal dynamic decision making, but is normally difficult to test empirically without knowledge of the decision-maker's preference function. In the experiment reported here we use a new experimental procedure to get round this difficulty, (...) which also enables us to shed some light on the decision process that the decision-maker is using if he or she is not using the Principle of Optimality - which appears to be the case in our experiments. (shrink)

This article challenges the general thesis that an unconditional basic income, set at the highest sustainable level, is required for maximizing the income-leisure opportunities of the least advantaged, when income varies according to the responsible factor of labor input. In a linear optimal taxation model (of a type suggested by Vandenbroucke 2001) in which opportunities depend only on individual productivity, adding the instrument of a uniform wage subsidy generates an array of undominated policies besides the basic income maximizing policy, (...) including a “zero basic income” policy which equalizes the post-tax wage rate. The choice among such undominated policies may be guided by distinct normative criteria which supplement the maximin objective in various ways. It is shown that most of these criteria will be compatible with, or actually select, the zero basic income policy and reject the basic income maximizing one. In view of the model's limited realism, the force of this main conclusion is discussed both in relation to Van Parijs' argument for basic income in Real Freedom for All (1995) and to some key empirical conditions in the real world. Footnotes1 I am grateful for useful comments on various stages of this paper by Marc Fleurbaey, Susan Hurley, Mathias Hild, Dirk Van de gaer, Frank Vandenbroucke, Alex Voorhoeve, Roland van der Veen, Andrew Williams, Chris Woodard and an anonymous referee. Above all I thank Loek Groot for his contribution. The research has also been supported by the Netherlands Organization for Scientific Research (NWO), and the Social and Political Theory Program of the Research School of Social Sciences, Australian National University. (shrink)

We provide an economic interpretation of the practice consisting in incorporating risk measures as constraints in an expected prospect maximization problem. For what we call the infimum of expectations class of risk measures, we show that if the decision maker (DM) maximizes the expectation of a random prospect under constraint that the risk measure is bounded above, he then behaves as a “generalized expected utility maximizer” in the following sense. The DM exhibits ambiguity with respect to a family of utility (...) functions defined on a larger set of decisions than the original one; he adopts pessimism and performs first a minimization of expected utility over this family, then performs a maximization over a new decisions set. This economic behaviour is called “maxmin under risk” and studied by Maccheroni (Econ Theory 19:823–831, 2002). As an application, we make the link between an expected prospect maximization problem, subject to conditional value-at-risk being less than a threshold value, and a non-expected utility economic formulation involving “loss aversion”-type utility functions. (shrink)

The most conceptually drastic change in natural language syntactic theory in recent years is the introduction of economy conditions (ECs). Although there is not a unified formal notion of economy, the intuition is that natural languages are governed by a general “less is more” principle. Those who take this seriously, and regard it not just as principle guiding the researcher but as something to be implemented directly in grammars, are often led to comparative economy conditions (comparative ECs), which (...) select from a set of structures the most economical among them according to some criterion. Such conditions are associated with the Minimalist Program (MP), but they are found also in Optimality Theory (OT) and Lexical-Functional Grammar (LFG).1 The following is a sample of the prominent works mentioning ‘economy’. (shrink)

We test people's ability to optimize performance across two concurrent tasks. Participants performed a number entry task while controlling a randomly moving cursor with a joystick. Participants received explicit feedback on their performance on these tasks in the form of a single combined score. This payoff function was varied between conditions to change the value of one task relative to the other. We found that participants adapted their strategy for interleaving the two tasks, by varying how long they spent (...) on one task before switching to the other, in order to achieve the near maximum payoff available in each condition. In a second experiment, we show that this behavior is learned quickly and remained stable for as long as the payoff function did not change. The results of this work show that people are adaptive and flexible in how they prioritize and allocate attention in a dual-task setting. However, it also demonstrates some of the limits regarding people's ability to optimize payoff functions. (shrink)

Conversational contextualism states that the truth-conditions expressed by knowledge-attributing sentences vary relative to the context of utterance. This context is determined partly by different standards the person involved must meet in order to make the sentence true. I am concerned with the question of how these standards can be raised or lowered, and especially what happens to the standards and the conversational score when parties in a discussion push the conversational scores in different directions. None of the available options (...) for an answer seems satisfying. I argue that this results from a misunderstanding of the characteristics of the situation at hand. (shrink)

The Automated External Defibrillator (AED) is an intuitive device used by witnesses of an incident without medical training in cases of sudden cardiac arrest. Its operation consists in delivering an electrical pulse to the cardiac conduction system, as a result of which normal heart rate is restored. The lack of awareness in society concerning the usefulness of the device and the inadequate deployment of AEDs result in their too infrequent application by witnesses of incidents. The aim of this paper is (...) to verify whether cluster analysis is the appropriate statistical method to determine the appropriate deployment of AED devices on the basis of cases of sudden cardiac arrest in out-of-hospital conditions. The initial cluster analysis showed the validity of using the method in question for planning the appropriate locations of AEDs. (shrink)

Lou Goble proposed powerful conditional deontic logics (CDPM) that are able to deal with deontic conflicts by means of restricting the inheritance principle. One of the central problems for dyadic deontic logics is to properly treat the restricted applicability of the principle “strengthening the antecedent”. In most cases it is desirable to derive from an obligation A under condition B, that A is also obliged under condition B and C. However, there are important counterexamples. Goble proposed a weakened rational monotonicity (...) principle to tackle this problem. This solution is suboptimal as it is for some examples counter-intuitive or even leads to explosion. The paper identifies also other problems of Goble’s systems. For instance, to make optimal use of the restricted inheritance principle, in many cases the user has to manually add certain statements to the premises. An adaptive logic framework based on CDPM is proposed which is able to tackle these problems. It allows for certain rules to be applied as much as possible. In this way counter-intuitive consequences as well as explosion can be prohibited and no user interference is required. Furthermore, for non-conflicting premise sets the adaptive logics are equivalent to Goble’s dyadic version of standard deontic logic. (shrink)

In this paper the arguments for optimal data selection and the contrast class account of negations in the selection task and the conditional inference task are summarised, and contrasted with the matching bias approach. It is argued that the probabilistic contrast class account provides a unified, rational explanation for effects across these tasks. Moreover, there are results that are only explained by the contrast class account that are also discussed. The only major anomaly is the explicit negations effect in (...) the selection task (Evans, Clibbens, & Rood, 1996), which it is argued may not be the result of normal interpretative processes. It is concluded that the effects of negation on human reasoning provide good evidence for the view that human reasoning processes may be rational according to a probabilistic standard. (shrink)