Prediction
In: http://hdl.handle.net/10945/46660
Adapted and extended from an address to the Military Applications Society of INFORMS delivered in Monterey CA on 27 March 2012.
Neurons in the orbitofrontal cortex (OFC) fire in anticipation of and during rewards. Such firing has been suggested to encode reward predictions and to account in some way for the role of this area in adaptive behavior and learning. However, it has also been reported that neural activity in OFC reflects reward prediction errors, which might drive learning directly. Here we tested this question by analyzing the firing of OFC neurons recorded in an odor discrimination task in which rats were trained to sample odor cues and respond left or right on each trial for reward. Neurons were recorded across blocks of trials in which we switched either the number or the flavor of the reward delivered in each well. Previously we have described how neurons in this dataset fired to the predictive cues (Stalnaker et al., 2014); here we focused on the firing in anticipation of and just after delivery of each drop of reward, looking specifically for differences in firing based on whether the reward number or flavor was unexpected or expected. Unlike dopamine neurons recorded in this setting, which exhibited phasic error-like responses after surprising changes in either reward number or reward flavor (Takahashi et al., 2017), OFC neurons showed no such error correlates and instead fired in a way that reflected reward predictions. Copyright 2018 ; This work was supported by funding from NIDA . The opinions expressed in this article are the authors' own and do not reflect the view of the National Institutes of Health, the Department of Health and Human Services, or the United States government. ; https://dx.doi.org/10.1016/j.nlm.2018.01.013
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Prediction markets sind generell bekannt als ein Sondertyp der Kapitalmärkte, an welchen der Wert der gehandelten Vermögenswerte durch den Ausgang von unsicheren, zukünftigen Ereignissen bedingt wird. Die Masterarbeit hat sich zum Ziel gesetzt, die berichtenswertesten Anwendungsbefunde in Bezug auf Prediction markets systematisch vorzustellen. Um dies zu verwirklichen wurde folgende Forschungsfrage formuliert: Was sind die berichtenswertesten Anwendungsbereiche für Prediction Markets und welche Verhaltensaspekte der Menschen zeigen sich bei der Verwendung derartiger Prognosemechanismen? Die Masterarbeit untersucht und stellt methodologisch zusammen sowohl die neuesten akademischen Ansätze, als auch die praktischen Implementationen von Prediction Markets mit dem Ziel, diesem wenig systematisierten Wissenschaftsfeld eine gewisse Kontinuität zu verschaffen. Politik, Sport und zahlreiche Anwendungen innerhalb verschiedenen Unternehmen stellen den Kern dieser Masterarbeit dar und liefern folgende Befunde: Im Bereich der Vorhersage politischer Ereignisse liefern Prediction Markets regelmäßig bessere Leistungen als Umfragen und Experten. Im Sportbereich sind Prediction Markets in der Lage, die allgemeine Auffassung über die Prognosefähigkeit der Wettquoten zu widerlegen. Anwendungsbeispiele aus der Praxis liefern glaubwürdige Belege dafür, dass Prediction Markets erfolgreich verstreute Information aggregieren können. Favorite longshot bias, reverse favorite longshot bias, herding bias und optimistic bias sind Verhaltensmuster, die durchgehend festgestellt werden können. Auf der negativen Seite sind das Nichtvorhandensein eines geeigneten Benchmark-Mechanismus, ein experimenteller Charakter und das Fehlen rechtlicher Rahmenbedingungen hervorzuheben. Die fehlende Übereinstimmung über theoretische Grundlagen, weitere konkrete Anwendungen und allgemeine Popularisierung der Thematik drängen sich schließlich als forschungsbedürftige Themen auf. ; Prediction markets are generally being referred to as a special case of asset markets where the value of the traded asset is contingent upon the outcome of some uncertain event at or before some pre-specified point in time. The master thesis aims at systematically presenting the newsworthiest application findings related to prediction markets. In order to succeed in such an endeavor, the following research question finds itself at the heart of the thesis: What are the newsworthiest prediction markets application fields, and which aspects of human behavior become apparent with the use of such forecasting mechanisms? The thesis compiles and methodically examines both the latest academic as well as practical efforts related to the application fields of prediction markets, with the aim of adding continuity to this still somewhat disorganized scientific field. Application fields of politics, sports and various types of corporate applications represent the core of the paper and provide the following findings: the field of politics shows that prediction markets are able to outperform polls and experts on a consistent basis. In the field of sports, prediction market studies refute the general belief that betting lines represent predictions. Numerous corporate applications provide substantial evidence for successful aggregation of scattered information and the use of collective wisdom. Behavioral patterns in the form of the favorite-longshot bias, reverse favorite-longshot bias, herding bias, and optimistic bias are consistently being detected throughout the different application fields. The frequent absence of an appropriate benchmark mechanism, an experimental character, and a deficiency of a legal framework come into the forefront on the negative side. To conclude, the thesis identifies the following topics as requiring further research: fundamental theoretical postulates, further practical implementations, and the popularization of the field. ; Miroslav Tepavac ; Zusammenfassungen in Deutsch und Englisch ; Karl-Franzens-Universität Graz, Masterarbeit, 2018 ; (VLID)2945882
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Scientists' responsibility to inform the public about their results may conflict with their responsibility not to cause social disturbance by the communication of these results. A study of the well-known Brady-Spence and Then Browning earthquake predictions illustrates this conflict in the publication of scientifically unwarranted predictions. Furthermore a public policy that considers public sensitivity caused by such publications as an opportunity to promote public awareness is ethically problematic from (i) a refined consequentialist point of view that any means cannot be justified by any ends, and (ii) a rights view according to which individuals should never be treated as a mere means to ends. The Parkfield experiment, the so-called paradigm case of cooperation between natural and social scientists and the political authorities in hazard management and risk communication, is also open to similar ethical criticism. For the people in the Parkfield area were not informed that the whole experiment was based on a contested seismological paradigm.
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International audience ; IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. IMPREX aimed to improve society's ability to anticipate and respond to future extreme hydrological events in Europe across a variety of uses in the water-related sectors (flood forecasting, drought risk assessment, agriculture, navigation, hydropower and water supply utilities). Through the engagement with stakeholders and continuous feedback between model outputs and water applications, progress was achieved in better understanding the way hydrological predictions can be useful to (and operationally incorporated into) problem-solving in the water sector. The work and discussions carried out during the project nurtured further reflections toward a common vision for hydrological prediction. In this article, we summarized the main findings of the IMPREX project within a broader overview of hydrological prediction, providing a vision for improving such predictions. In so doing, we first presented a synopsis of hydrological and weather forecasting, with a focus on medium-range to seasonal scales of prediction for increased preparedness. Second, the lessons learned from IMPREX were discussed. The key findings were the gaps highlighted in the global observing system of the hydrological cycle, the degree of accuracy of hydrological models and the techniques of post-processing to correct biases, the origin of seasonal hydrological skill in Europe and user requirements of hydrometeorological forecasts to ensure their appropriate use in decision-making models and practices. Last, a vision for how to improve these forecast systems/products in the future was expounded, including advancing numerical weather and hydrological models, improved earth monitoring and more frequent interaction between forecasters and users to tailor the forecasts to applications. We conclude that if these improvements can be implemented in the coming years, earth ...
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International audience ; IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. IMPREX aimed to improve society's ability to anticipate and respond to future extreme hydrological events in Europe across a variety of uses in the water-related sectors (flood forecasting, drought risk assessment, agriculture, navigation, hydropower and water supply utilities). Through the engagement with stakeholders and continuous feedback between model outputs and water applications, progress was achieved in better understanding the way hydrological predictions can be useful to (and operationally incorporated into) problem-solving in the water sector. The work and discussions carried out during the project nurtured further reflections toward a common vision for hydrological prediction. In this article, we summarized the main findings of the IMPREX project within a broader overview of hydrological prediction, providing a vision for improving such predictions. In so doing, we first presented a synopsis of hydrological and weather forecasting, with a focus on medium-range to seasonal scales of prediction for increased preparedness. Second, the lessons learned from IMPREX were discussed. The key findings were the gaps highlighted in the global observing system of the hydrological cycle, the degree of accuracy of hydrological models and the techniques of post-processing to correct biases, the origin of seasonal hydrological skill in Europe and user requirements of hydrometeorological forecasts to ensure their appropriate use in decision-making models and practices. Last, a vision for how to improve these forecast systems/products in the future was expounded, including advancing numerical weather and hydrological models, improved earth monitoring and more frequent interaction between forecasters and users to tailor the forecasts to applications. We conclude that if these improvements can be implemented in the coming years, earth system and hydrological modelling will become more skillful, thus leading to socioeconomic benefits for the citizens of Europe and beyond.
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Nowadays social media like Twitter and Facebook etc. is one of the key players. Twitters are micro blogging sites by which users sent their opinions and views in brief. The information generated by one user can be seen by everyone. Therefore to analyze twitter sentiment can be a crucial task. For this task, we have used various approaches like novel based approach and machine learning and many other rules like context awareness are used for the detection of public opinion and prediction of results. We are studying the user tweets during elections. Meaningful tweets are collected on a definite period.The feasibility of the developed classification model is identified by our proposed work to identify the political orientation on the tweets and other user-based features. The technique for the collection of tweets in time has played an important role. When the outcome of applied technique competes with survey agencies result was published before elections result.
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IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. IMPREX aimed to improve society's ability to anticipate and respond to future extreme hydrological events in Europe across a variety of uses in the water-related sectors (flood forecasting, drought risk assessment, agriculture, navigation, hydropower and water supply utilities). Through the engagement with stakeholders and continuous feedback between model outputs and water applications, progress was achieved in better understanding the way hydrological predictions can be useful to (and operationally incorporated into) problem-solving in the water sector. The work and discussions carried out during the project nurtured further reflections toward a common vision for hydrological prediction. In this article, we summarized the main findings of the IMPREX project within a broader overview of hydrological prediction, providing a vision for improving such predictions. In so doing, we first presented a synopsis of hydrological and weather forecasting, with a focus on medium-range to seasonal scales of prediction for increased preparedness. Second, the lessons learned from IMPREX were discussed. The key findings were the gaps highlighted in the global observing system of the hydrological cycle, the degree of accuracy of hydrological models and the techniques of post-processing to correct biases, the origin of seasonal hydrological skill in Europe and user requirements of hydrometeorological forecasts to ensure their appropriate use in decision-making models and practices. Last, a vision for how to improve these forecast systems/products in the future was expounded, including advancing numerical weather and hydrological models, improved earth monitoring and more frequent interaction between forecasters and users to tailor the forecasts to applications. We conclude that if these improvements can be implemented in the coming years, earth system and hydrological modelling will become more skillful, thus leading to socioeconomic benefits for the citizens of Europe and beyond.
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In: https://eprints.ucm.es/id/eprint/49891/1/T40534.pdf
The dissertation is entitled: "Essays on information and prediction" and consists of a total of four chapters. The central issue is the study of the role that certain mechanisms of aggregation of information, such as predictive markets or elections, can play in improving the accuracy of predictive algorithms. The first chapter of the thesis is entitled: "Economic Determinants of Political Alternation: A Panel Data Analysis of OECD Countries" and studies the relationship between economic performance and political alternation. The initial hypothesis is that the stochastic process that determines the political alternation is not independent of the economy, so that the recent evolution of the macroeconomic variables would be very relevant when explaining the electoral results. We are implicitly considering the "responsibility hypothesis", by which voters are aware of the economic information since they consider that the government is responsible, through its actions, for the good or bad economic situation of the country. In this way, economic variables can predict the probability of political alternation. Throughout the chapter, a critical review of the literature is presented, with special attention to the article Brender & Drazen (2008) and later the estimation of a re-election probability model is proposed, using macroeconomic indicators. The contributions of this chapter to literature are diverse. On the one hand, the results obtained contradict those found in the "economic vote" literature. On the other hand, there are also methodological contributions: the use of a discount rate to allow voters to give more weight to the most recent data, propose an alternative way of measuring political alternation and the use of structural deficit data to solve the problem of multicollinearity between the independent variables.
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The continuing development of prediction markets is important because of their success in foretelling the future in politics, economics, and science. In this article, we identify the expressive elements inherent in prediction markets and explore how legislation such as the Unlawful Internet Gambling Enforcement Act of 2006 might harm such predictive speech. This article is the first to explore First Amendment protections for prediction markets in such depth, and in so doing, we distinguish prediction markets from other regulated areas such as gambling and securities trading. The article's examination of prediction markets also illustrates the limitations of current commercial speech doctrine. We conclude by discussing how the executive, legislative, and judicial branches might resolve the First Amendment challenges of regulating prediction markets, and we propose a new legal test, modeled on existing free speech jurisprudence, which may assist courts in adjudicating any constitutional challenges.
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IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. Its aim was to improve society's ability to anticipate and respond to future extreme hydrological events in Europe across a variety of uses in the water-related sectors (flood forecasting, drought risk assessment, agriculture, navigation, hydropower, and water supply utilities). Through the engagement with stakeholders and continuous feedback between model outputs and water applications, progress was achieved in better understanding the way hydrological predictions can be useful to (and operationally incorporated into) problem solving in the water sector. The work and discussions carried out during the project nurtured further reflections towards a common vision for hydrological prediction. In this article, we summarize the main findings of the IMPREX project within a broader overview of hydrological prediction, providing a vision for improving such predictions. In so doing, we firstly present a synopsis of hydrological and weather forecasting, with a focus on medium-range to seasonal scales of prediction for increased preparedness. Second, the lessons learnt from IMPREX are discussed. The key findings are the gaps highlighted in the global observing system of the hydrological cycle, the degree of accuracy of hydrological models and the techniques of post-processing to correct biases, the origin of seasonal hydrological skill in Europe, and user requirements of hydrometeorological forecasts to ensure their appropriate use in decision-making models and practices. Lastly, a vision for how to improve these forecast systems/products in the future is expounded and these include advancing numerical weather and hydrological models, improved earth monitoring, and more frequent interaction between forecasters and users to tailor the forecasts to applications. We conclude that if these improvements can be implemented in the coming years, earth system and ...
BASE
IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. IMPREX aimed to improve society's ability to anticipate and respond to future extreme hydrological events in Europe across a variety of uses in the water-related sectors (flood forecasting, drought risk assessment, agriculture, navigation, hydropower and water supply utilities). Through the engagement with stakeholders and continuous feedback between model outputs and water applications, progress was achieved in better understanding the way hydrological predictions can be useful to (and operationally incorporated into) problem-solving in the water sector. The work and discussions carried out during the project nurtured further reflections toward a common vision for hydrological prediction. In this article, we summarized the main findings of the IMPREX project within a broader overview of hydrological prediction, providing a vision for improving such predictions. In so doing, we first presented a synopsis of hydrological and weather forecasting, with a focus on medium-range to seasonal scales of prediction for increased preparedness. Second, the lessons learned from IMPREX were discussed. The key findings were the gaps highlighted in the global observing system of the hydrological cycle, the degree of accuracy of hydrological models and the techniques of post-processing to correct biases, the origin of seasonal hydrological skill in Europe and user requirements of hydrometeorological forecasts to ensure their appropriate use in decision-making models and practices. Last, a vision for how to improve these forecast systems/products in the future was expounded, including advancing numerical weather and hydrological models, improved earth monitoring and more frequent interaction between forecasters and users to tailor the forecasts to applications. We conclude that if these improvements can be implemented in the coming years, earth system and hydrological modelling will become more skillful, thus leading to socioeconomic benefits for the citizens of Europe and beyond.
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In the light of the scholarly standards development, research methods and their implications of theoretical literature, this study aims at answering the focal question suggested here: How far is prediction manifested in international relations? This study also throws light on the ongoing controversy of prediction in the context of international relations. Such debate will be unveiled through descriptive and analytical methods which in turn place an adequate emphasis on examining the controversial and theoretical issues raised by the concern of prediction. Relevant examples in the same context will be also given such as: the predictions suggested by the New Realism, Structuralism, and how far such theories recognize the international policies. The pragmatic implications dwells on the concept of prediction in international relations through identifying prediction's standards and its indications, the appropriate framework to make up theory, implications fields, assumptions prioritization, and the relation between the theoretical concepts to come up with a theory of valid for prediction in the future. The study concludes that the perpetual change of international system's frameworks brings about an urgent use of the methodological signs of prediction to strike a balance and maintain stability in the international environment. Such state of balance gives room for the hegemonic international terms and world peace since prediction phenomenon has been manipulated by scholarly research and methodological tactics.
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