There is a long-standing disagreement in the philosophy of probability and Bayesian decision theory about whether an agent can hold a meaningful credence about an upcoming action, while she deliberates about what to do. Can she believe that it is, say, 70% probable that she will do A, while she chooses whether to do A? No, say some philosophers, for Deliberation Crowds Out Prediction (DCOP), but others disagree. In this paper, we propose a valid core for DCOP, and identify terminological (...) causes for some of the apparent disputes. (shrink)

Can an agent deliberating about an action A hold a meaningful credence that she will do A? 'No', say some authors, for 'Deliberation Crowds Out Prediction' (DCOP). Others disagree, but we argue here that such disagreements are often terminological. We explain why DCOP holds in a Ramseyian operationalist model of credence, but show that it is trivial to extend this model so that DCOP fails. We then discuss a model due to Joyce, and show that Joyce's rejection of DCOP rests (...) on terminological choices about terms such as 'intention', 'prediction', and 'belief'. Once these choices are in view, they reveal underlying agreement between Joyce and the DCOP-favouring tradition that descends from Ramsey. Joyce's Evidential Autonomy Thesis (EAT) is effectively DCOP, in different terminological clothing. Both principles rest on the so-called 'transparency' of first-person present-tensed reflection on one's own mental states. (shrink)

The urgent drive for vaccine development in the midst of the current COVID-19 pandemic has prompted public and private organisations to invest heavily in research and development of a COVID-19 vaccine. Organisations globally have affirmed the commitment of fair global access, but the means by which a successful vaccine can be mass produced and equitably distributed remains notably unanswered. Barriers for low-income countries include the inability to afford vaccines as well as inadequate resources to vaccinate, barriers that are exacerbated during (...) a pandemic. Fair distribution of a pandemic vaccine is unlikely without a solid ethical framework for allocation. This piece analyses four allocation paradigms: ability to develop or purchase; reciprocity; ability to implement; and distributive justice, and synthesises their ethical considerations to develop an allocation model to fit the COVID-19 pandemic. (shrink)

In his classic book “the Foundations of Statistics” Savage developed a formal system of rational decision making. The system is based on (i) a set of possible states of the world, (ii) a set of consequences, (iii) a set of acts, which are functions from states to consequences, and (iv) a preference relation over the acts, which represents the preferences of an idealized rational agent. The goal and the culmination of the enterprise is a representation theorem: Any preference relation that (...) satisfies certain arguably acceptable postulates determines a (finitely additive) probability distribution over the states and a utility assignment to the consequences, such that the preferences among acts are determined by their expected utilities. Additional problematic assumptions are however required in Savage's proofs. First, there is a Boolean algebra of events (sets of states) which determines the richness of the set of acts. The probabilities are assigned to members of this algebra. Savage's proof requires that this be a σ-algebra (i.e., closed under infinite countable unions and intersections), which makes for an extremely rich preference relation. On Savage's view we should not require subjective probabilities to be σ-additive. He therefore finds the insistence on a σ-algebra peculiar and is unhappy with it. But he sees no way of avoiding it. Second, the assignment of utilities requires the constant act assumption: for every consequence there is a constant act, which produces that consequence in every state. This assumption is known to be highly counterintuitive. The present work contains two mathematical results. The first, and the more difficult one, shows that the σ-algebra assumption can be dropped. The second states that, as long as utilities are assigned to finite gambles only, the constant act assumption can be replaced by the more plausible and much weaker assumption that there are at least two non-equivalent constant acts. The second result also employs a novel way of deriving utilities in Savage-style systems -- without appealing to von Neumann-Morgenstern lotteries. The paper discusses the notion of “idealized agent" that underlies Savage's approach, and argues that the simplified system, which is adequate for all the actual purposes for which the system is designed, involves a more realistic notion of an idealized agent. (shrink)

Causalists and Evidentialists can agree about the right course of action in an (apparent) Newcomb problem, if the causal facts are not as initially they seem. If declining $1,000 causes the Predictor to have placed $1m in the opaque box, CDT agrees with EDT that one-boxing is rational. This creates a difficulty for Causalists. We explain the problem with reference to Dummett's work on backward causation and Lewis's on chance and crystal balls. We show that the possibility that the causal (...) facts might be properly judged to be non-standard in Newcomb problems leads to a dilemma for Causalism. One horn embraces a subjectivist understanding of causation, in a sense analogous to Lewis's own subjectivist conception of objective chance. In this case the analogy with chance reveals a terminological choice point, such that either (i) CDT is completely reconciled with EDT, or (ii) EDT takes precedence in the cases in which the two theories give different recommendations. The other horn of the dilemma rejects subjectivism, but now the analogy with chance suggests that it is simply mysterious why causation so construed should constrain rational action. (shrink)

This paper proposes an innovative ducted fan aerial manipulator, which is particularly suitable for the tasks in confined environment, where traditional multirotors and helicopters would be inaccessible. The dynamic model of the aerial manipulator is established by comprehensive mechanism and parametric frequency-domain identification. On this basis, a composite controller of the aerial platform is proposed. A basic static robust controller is designed via H-infinity synthesis to achieve basic performance, and an adaptive auxiliary loop is designed to estimate and compensate for (...) the effect acting on the vehicle from the manipulator. The computer simulation analyses show good stability of the aerial vehicle under the manipulator motion and good tracking performance of the manipulator end effector, which verify the feasibility of the proposed aerial manipulator design and the effectiveness of the proposed controller, indicating that the system can meet the requirements of high precision operation tasks well. (shrink)

This paper offers a fine analysis of different versions of the well known sure-thing principle. We show that Savage's formal formulation of the principle, i.e., his second postulate (P2), is strictly stronger than what is intended originally.

The event-triggered consensus control for leader-following multiagent systems subjected to external disturbances is investigated, by using the output feedback. In particular, a novel distributed event-triggered protocol is proposed by adopting dynamic observers to estimate the internal state information based on the measurable output signal. It is shown that under the developed observer-based event-triggered protocol, multiple agents will reach consensus with the desired disturbance attenuation ability and meanwhile exhibit no Zeno behaviors. Finally, a simulation is presented to verify the obtained results.

Recently, infrared human action recognition has attracted increasing attention for it has many advantages over visible light, that is, being robust to illumination change and shadows. However, the infrared action data is limited until now, which degrades the performance of infrared action recognition. Motivated by the idea of transfer learning, an infrared human action recognition framework using auxiliary data from visible light is proposed to solve the problem of limited infrared action data. In the proposed framework, we first construct a (...) novel Cross-Dataset Feature Alignment and Generalization framework to map the infrared data and visible light data into a common feature space, where Kernel Manifold Alignment and a dual aligned-to-generalized encoders model are employed to represent the feature. Then, a support vector machine is trained, using both the infrared data and visible light data, and can classify the features derived from infrared data. The proposed method is evaluated on InfAR, which is a publicly available infrared human action dataset. To build up auxiliary data, we set up a novel visible light action dataset XD145. Experimental results show that the proposed method can achieve state-of-the-art performance compared with several transfer learning and domain adaptation methods. (shrink)

Savage's framework of subjective preference among acts provides a paradigmatic derivation of rational subjective probabilities within a more general theory of rational decisions. The system is based on a set of possible states of the world, and on acts, which are functions that assign to each state a consequence€. The representation theorem states that the given preference between acts is determined by their expected utilities, based on uniquely determined probabilities (assigned to sets of states), and numeric utilities assigned to consequences. (...) Savage's derivation, however, is based on a highly problematic well-known assumption not included among his postulates: for any consequence of an act in some state, there is a "constant act" which has that consequence in all states. This ability to transfer consequences from state to state is, in many cases, miraculous -- including simple scenarios suggested by Savage as natural cases for applying his theory. We propose a simplification of the system, which yields the representation theorem without the constant act assumption. We need only postulates P1-P6. This is done at the cost of reducing the set of acts included in the setup. The reduction excludes certain theoretical infinitary scenarios, but includes the scenarios that should be handled by a system that models human decisions. (shrink)

Achieving the global benefits of artificial intelligence will require international cooperation on many areas of governance and ethical standards, while allowing for diverse cultural perspectives and priorities. There are many barriers to achieving this at present, including mistrust between cultures, and more practical challenges of coordinating across different locations. This paper focuses particularly on barriers to cooperation between Europe and North America on the one hand and East Asia on the other, as regions which currently have an outsized impact on (...) the development of AI ethics and governance. We suggest that there is reason to be optimistic about achieving greater cross-cultural cooperation on AI ethics and governance. We argue that misunderstandings between cultures and regions play a more important role in undermining cross-cultural trust, relative to fundamental disagreements, than is often supposed. Even where fundamental differences exist, these may not necessarily prevent productive cross-cultural cooperation, for two reasons: cooperation does not require achieving agreement on principles and standards for all areas of AI; and it is sometimes possible to reach agreement on practical issues despite disagreement on more abstract values or principles. We believe that academia has a key role to play in promoting cross-cultural cooperation on AI ethics and governance, by building greater mutual understanding, and clarifying where different forms of agreement will be both necessary and possible. We make a number of recommendations for practical steps and initiatives, including translation and multilingual publication of key documents, researcher exchange programmes, and development of research agendas on cross-cultural topics. (shrink)

In countries such as China, where Confucianism is the backbone of national culture, high-social-status entrepreneurs are inclined to engage in corporate social responsibility activities due to the perceived high stress from stakeholders and high ability of doing CSR. Based on a large-scale survey of private enterprises in China, our paper finds that Chinese entrepreneurs at private firms who have high social status are prone to engage in social responsibility efforts. In addition, high-social-status Chinese entrepreneurs are even more likely to engage (...) in social responsibility efforts as they become more politically connected and as the region becomes more market-oriented. These findings extend the upper echelons perspective of CSR into Chinese context by shedding light on antecedents of CSR from a new perspective and clarifying the boundary conditions of the social status–CSR link from the institutional perspective. (shrink)

There are two accounts of how readers of unspaced writing systems know where to move their eyes: saccades are directed toward default targets ; or saccade lengths are adjusted dynamically, as a function of ongoing parafoveal processing. This article reports an eye-movement experiment supporting the latter hypothesis by demonstrating that the slope of the relationship between the saccade launch site on word N and the subsequent fixation landing site on word N + 1 is > 1, suggesting that saccades are (...) lengthened from launch sites that afford more parafoveal processing. This conclusion is then evaluated and confirmed via simulations using implementations of both hypotheses, with a discussion of these results for our understanding of saccadic targeting during reading and existing models of eye-movement control. (shrink)

The quality factor is an important parameter for measuring the attenuation of seismic waves. Reliable [Formula: see text] estimation and stable inverse [Formula: see text] filtering are expected to improve the resolution of seismic data and deep-layer energy. Many methods of estimating [Formula: see text] are based on an individual wavelet. However, it is difficult to extract the individual wavelet precisely from seismic reflection data. To avoid this problem, we have developed a method of directly estimating [Formula: see text] from (...) reflection data. The core of the methodology is selecting the peak-frequency points to linear fit their logarithmic spectrum and time-frequency product. Then, we calculated [Formula: see text] according to the relationship between [Formula: see text] and the optimized slope. First, to get the peak frequency points at different times, we use the generalized S transform to produce the 2D high-precision time-frequency spectrum. According to the seismic wave attenuation mechanism, the logarithmic spectrum attenuates linearly with the product of frequency and time. Thus, the second step of the method is transforming a 2D spectrum into 1D by variable substitution. In the process of transformation, we only selected the peak frequency points to participate in the fitting process, which can reduce the impact of the interference on the spectrum. Third, we obtain the optimized slope by least-squares fitting. To demonstrate the reliability of our method, we applied it to a constant [Formula: see text] model and the real data of a work area. For the real data, we calculated the [Formula: see text] curve of the seismic trace near a well and we get the high-resolution section by using stable inverse [Formula: see text] filtering. The model and real data indicate that our method is effective and reliable for estimating the [Formula: see text] value. (shrink)

Time theft is a costly burden on organizations. However, there is limited knowledge about why time theft occurs. To advance this line of research, this conceptual paper looks at the association between organizational injustice and time theft from identity, moral, and equity perspectives. This paper proposes that organizational injustice triggers time theft through decreased organizational identification. It also proposes that moral disengagement and equity sensitivity moderate this process such that organizational identification is less likely to mediate among employees with high (...) moral disengagement and more likely to mediate among employees who are equity sensitives and entitleds. (shrink)

Grounded in Bandura’s social cognitive theory of moral thought and action, we develop a conceptual model linking supervisors’ perceptions of organizational injustice and abusive supervision with moral disengagement mechanisms acting as the underlying process. Specifically, we elaborate why and how supervisors’ experiences of each type of injustice would trigger their adoption of distinctive moral disengagement mechanisms, which in turn lead to their abusive supervisory conduct. The present conceptual model sheds new light on linking organizational injustice to abusive supervision from a (...) moral perspective. In addition, it also provides important theoretical and managerial implications to our current understanding of why and how abusive supervision happens. (shrink)

The recent rapid development of information technology, such as sensing technology, communications technology, and database, allows us to use simulation experiments for analyzing serious accidents caused by hazardous chemicals. Due to the toxicity and diffusion of hazardous chemicals, these accidents often lead to not only severe consequences and economic losses, but also traffic jams at the same time. Emergency evacuation after hazardous chemical accidents is an effective means to reduce the loss of life and property and to smoothly resume the (...) transport network as soon as possible. This paper considers the dynamic changes of the hazardous chemicals’ concentration after their leakage and simulates the diffusion process. Based on the characteristics of emergency evacuation of hazardous chemical accidents, we build a mixed-integer programming model and design a heuristic algorithm using network optimization and diffusion simulation. We then verify the validity and feasibility of the algorithm using Jinan, China, as a computational example. In the end, we compare the results from different scenarios to explore the key factors affecting the effectiveness of the evacuation process. (shrink)

We developed an integrated method that can better constrain subsalt tomography using geology, thermal history modeling, and rock-physics principles. This method, called rock-physics-guided velocity modeling for migration uses predicted pore pressure as a guide to improve the quality of the earth model. We first generated a rock-physics model that provided a range of plausible pore pressure that lies between hydrostatic and fracture pressure. The range of plausible pore pressures was then converted into a range of plausible depth varying velocities as (...) a function of pore pressure that is consistent with geology and rock physics. Such a range of plausible velocities is called the rock-physics template. Such a template was then used to flatten the seismic gathers. We call this the pore-pressure scan technique. The outcome of the pore-pressure scan process was an “upper” and “lower” bound of pore pressure for a given earth model. Such velocity bounds were then used as constraints on the subsequent tomography, and further iterations were carried out. The integrated method not only flattened the common image point gathers but also limited the velocity field to its physically and geologically plausible range without well control; for example, in the study area it produced a better image and pore-pressure prognosis below salt. We determined that geologic control is essential, and we used it for stratigraphy, structure, and unconformity, etc. The method had several subsalt applications in the Gulf of Mexico and proved that subsalt pore pressure can be reliably predicted. (shrink)

Challenge-oriented organizational citizenship behavior or the organization-improving tasks employees perform beyond their job description is important for high organizational performance, but the organizational factors influencing it are poorly understood. In this study, we explored how inclusive leadership influences employees’ challenge-oriented organizational citizenship behavior in the Chinese context, drawing on data from 558 employees in high-tech industries. Multivariate correlation analysis showed that inclusive leadership promotes employees’ challenge-oriented organizational citizenship behavior and that this influence is partly mediated by work engagement. Further, it (...) showed that organizational innovative atmosphere has a moderating effect on the relationship between inclusive leadership and employees’ challenge-oriented organizational citizenship behavior. In effect, this study expands the range of predictive variables for challenge-oriented organizational citizenship behavior and provides not only theoretical insight but also practical guidance for leaders who seek to motivate this behavior in their employees. (shrink)

Epilepsy is a neurological disease, and the location of a lesion before neurosurgery or invasive intracranial electroencephalography surgery using intracranial electrodes is often very challenging. The high-frequency oscillation mode in MEG signal can now be used to detect lesions. Due to the time-consuming and error-prone operation of HFOs detection, an automatic HFOs detector with high accuracy is very necessary in modern medicine. Therefore, an optimized capsule neural network was used, and a MEG HFOs detector based on MEGNet was proposed to (...) facilitate the clinical detection of HFOs. To the best of our knowledge, this is the first time that a neural network has been used to detect HFOs in MEG. After optimized configuration, the accuracy, precision, recall, and F1-score of the proposed detector reached 94%, 95%, 94%, and 94%, which were better than other classical machine learning models. In addition, we used the k-fold cross-validation scheme to test the performance consistency of the model. The distribution of various performance indicators shows that our model is robust. (shrink)

An increasing number of the renowned company’s investors are turning attention to stock prediction in the search for new efficient ways of hypothesizing about markets through the application of behavioral finance. Accordingly, research on stock prediction is becoming a popular direction in academia and industry. In this study, the goal is to establish a model for predicting stock price movement through knowledge graph from the financial news of the renowned companies. In contrast to traditional methods of stock prediction, our approach (...) considers the effects of event tuple characteristics on stocks on the basis of knowledge graph and deep learning. The proposed model and other feature selection models were used to perform feature extraction on the websites of Thomson Reuters and Cable News Network. Numerous experiments were conducted to derive evidence of the effectiveness of knowledge graph embedding for classification tasks in stock prediction. A comparison of the average accuracy with which the same feature combinations were extracted over six stocks indicated that the proposed method achieves better performance than that exhibited by an approach that uses only stock data, a bag-of-words method, and convolutional neural network. Our work highlights the usefulness of knowledge graph in implementing business activities and helping practitioners and managers make business decisions. (shrink)