Abstract. We investigate the problem of autonomous agents processing pieces of information that may be corrupted (tainted). Agents have the option of contacting a central database for a reliable check of the status of the message, but this procedure is costly and therefore should be used with parsimony. Agents have to evaluate the risk of being infected, and decide if and when communicating partners are affordable. Trustability is implemented as a personal (one-to-one) record of past contacts among agents, and as a mean-field monitoring of the level of message corruption. Moreover, this information is slowly forgotten in time, so that at the end everybody is checked against the database. We explore the behavior of a homogeneous system in the case of a fixed pool of spreaders of corrupted messages, and in the case of spontaneous appearance of corrupted messages.
Introduced a new calculation method (K-method) for cognitive maps. K - method consists of two consecutive steps. In the first stage, allocated subgraph composed of all paths from one selected node (concept) to another node (concept) from the cognitive map (directed weighted graph) . In the second stage, after the transition to an undirected graph (symmetrization adjacency matrix) the influence of one node to another calculated with Kirchhoff method. In the proposed method, there is no problem inherent in the impulse method. In addition to "pair" influence of one node to another, the average characteristics are introduced, allowing to calculate the impact of the selected node to all other nodes and the influence of all on the one selected. For impulse method similar to the average characteristics in the case where the pulse method "works" are introduced and compared with the K-method.
We propose evolution rules of the multiagent network and determine statistical patterns in life cycle of agents - information messages. The main discussed statistical pattern is connected with the number of likes and reposts for a message. This distribution corresponds to Weibull distribution according to modeling results. We examine proposed model using the data from Twitter, an online social networking service.
Over the past 5 years, on behalf of state governments, nearly 100,000 Americans were gently manipulated by a team of social scientists. In 15 randomized, controlled trials, people in need of social services either encountered the standard application process or received a psychological nudge, in which the information was presented slightly differently—a postcard reminded them of deadlines, for example, or one choice was made easier than another. In 11 of the trials, the nudge modestly increased a person's response rate or influenced them to make financially smarter choices. The results, presented this week at a meeting in Chicago, add to the growing evidence that nudges developed by psychologists can make a real difference in the success of government programs.
It’s clear that regulated markets are not currently delivering the best outcomes for UK consumers. In the UK, we are collectively overpaying for mobile phone contracts by £355 million a year and almost 9.5 million households would be able to save over £300 each year by switching energy provider. In last week’s Queen’s Speech, the Government outlined its plans to bring forward a Better Markets Bill, to ‘open up markets, boost competition, give consumers more power and choice and make economic regulators work better.’ Here at the Behavioural Insights Team, we have been grappling with these issues over the past five years, and today we are publishing our latest, and most comprehensive, report covering this area: Applying behavioural insights to regulated markets, commissioned by Citizens Advice. In the report we set out a new vision, arguing that placing behavioural insights at the heart of regulation will reap significant benefits for consumers. Behavioural science offers both explanations for, and solutions to, behaviour that leads to consumers paying more than they need to and sticking with suppliers even when there are better deals and higher customer satisfaction elsewhere in the market. UK regulators are increasingly incorporating behavioural science into their approach, indeed the FCA has its own Behavioural Economics and Data Science Unit. However, we believe there are real opportunities to build upon the foundations already laid.
Abstract Beginning January 2014, Psychological Science gave authors the opportunity to signal open data and materials if they qualified for badges that accompanied published articles. Before badges, less than 3% of Psychological Science articles reported open data. After badges, 23% reported open data, with an accelerating trend; 39% reported open data in the first half of 2015, an increase of more than an order of magnitude from baseline. There was no change over time in the low rates of data sharing among comparison journals. Moreover, reporting openness does not guarantee openness. When badges were earned, reportedly available data were more likely to be actually available, correct, usable, and complete than when badges were not earned. Open materials also increased to a weaker degree, and there was more variability among comparison journals. Badges are simple, effective signals to promote open practices and improve preservation of data and materials by using independent repositories.
We propose that in strategic interactions a player is influenced by self-similarity. Self-similarity means that a player who chooses some action X tends to believe, to a greater extent than a player who chooses a different action, that other players will also choose action X. To demonstrate this phenomenon, we analyze the actions and the reported beliefs of players in a two-player two-action symmetric game. The game has the feature that for “materialistic” players, who wish to maximize their own payoff, there should be negative correlation between players’ actions and the beliefs that they assign to their opponent choosing the same action. We first elicit participants’ preferences over the outcomes of the game, and identify a large group of materialistic players. We then ask participants to choose an action in the game and report their beliefs. The reported beliefs of materialistic players are positively correlated with their actions, i.e., they are more likely to choose an action the stronger is their belief that their opponent will also choose the same action. We view this pattern as evidence for the presence of self-similarity.
Introduction Cell biologist Dr. Glen Rein had conceived of the idea that DNA would make a good target for testing healers’ ability to affect biological systems, since well established quantitative measures of DNA’s conformational state existed and it potentially offered a more stable and reliable system than cell or bacterial cultures. He had tested this model system with several healers by having them hold test tubes containing DNA while they attempted to create a healing environment, and had obtained some positive indicators that the conformational state of DNA changed when exposed to these environments. In late 1991, Dr. Rein accepted a position at the HeartMath Research Center with the intention of continuing these experiments in addition to a series of cell culture studies. We conducted a number of different experiments with DNA over the next year and a half. The first six months were primarily spent performing a series of control studies to insure the stability of the measurement system and refining the protocols. Doc Childre then added the element of intentionality to the protocols, which proved to be a key factor. Some of the key results of this series of studies were presented at research conferences and published in several conference proceedings.1-4 We have since received so many requests for the results of this research that we are now making a summary of our findings available in this brief report.
The third in a series of excerpts from Minds, Models and Milieux: Commemorating the Centennial of the Birth of Herbert Simon. Gerd Gigerenzer Herbert Simon left us with an unfinished task: a theory of bounded rationality. Such a theory should make two contributions. For one, it should describe how individuals and institutions actually make decisions. Understanding this process would advance beyond “as-if” theories of maximizing expected utility. Second, the theory should be able to deal with situations of uncertainty where “the conditions for rationality postulated by the model of neoclassical economics are not met” (Simon, 1989, p. 377). That is, it should extend to situations where one cannot calculate the optimal action but instead has to “satisfice,” that is, find either a better option than existing ones or one that meets a set aspiration level. This extension would make decision theory particularly relevant to the uncertain worlds of business, investment, and personal affairs.
Spending money so that it increases your happiness and wellbeing is an art form in itself. People who spend more on things that fit with their personality traits are happier, new research finds. For example, extroverted people are happier spending money in a restaurant. In contrast, the introverted get more pleasure from spending money in bookshops. A better fit between spending and personality was linked to life satisfaction more than total wealth or total spending. In other words: it matters less how much you have or how much you spend — what really matters is what you spend it on.
Tutti attivano delle distorsioni cognitive quando si relazionano con gli altri e conoscere quali sono può aiutare ad esserne consapevoli.Nessuno di noi è immune dalle distorsioni cognitive, tuttavia, essere consapevoli della loro esistenza può aiutare; una generica componente delle distorsioni cognitive è presente infatti in qualsiasi giudizio, in quanto esso è legato ad un fattore percettivo e dunque ad una visione della realtà filtrata soggettivamente da chi valuta.
Abstract People tend to hold overly favorable views of their abilities in many social and intellectual domains. The authors suggest that this overestimation occurs, in part, because people who are unskilled in these domains suffer a dual burden: Not only do these people reach erroneous conclusions and make unfortunate choices, but their incompetence robs them of the metacognitive ability to realize it. Across 4 studies, the authors found that participants scoring in the bottom quartile on tests of humor, grammar, and logic grossly overestimated their test performance and ability. Although their test scores put them in the 12th percentile, they estimated themselves to be in the 62nd. Several analyses linked this miscalibration to deficits in metacognitive skill, or the capacity to distinguish accuracy from error. Paradoxically, improving the skills of participants, and thus increasing their metacognitive competence, helped them recognize the limitations of their abilities.
Structural balance theory has been developed in sociology and psychology to explain how interacting agents, e.g., countries, political parties, opinionated individuals, with mixed trust and mistrust relationships evolve into polarized camps. Recent results have shown that structural balance is necessary for polarization in networks with fixed, strongly connected neighbor relationships when the opinion dynamics are described by DeGroot-type averaging rules. We develop this line of research in this paper in two steps. First, we consider fixed, not necessarily strongly connected, neighbor relationships. It is shown that if the network includes a strongly connected subnetwork containing mistrust, which influences the rest of the network, then no opinion clustering is possible when that subnetwork is not structurally balanced; all the opinions become neutralized in the end. In contrast, it is shown that when that subnetwork is indeed structurally balanced, the agents of the subnetwork evolve into two polarized camps and the opinions of all other agents in the network spread between these two polarized opinions. Second, we consider time-varying neighbor relationships. We show that the opinion separation criteria carry over if the conditions for fixed graphs are extended to joint graphs. The results are developed for both discrete-time and continuous-time models.
What drives the propensity for the social network dynamics? Social influence is believed to drive both off-line and on-line human behavior, however it has not been considered as a driver of social network evolution. Our analysis suggest that, while the network structure affects the spread of influence in social networks, the network is in turn shaped by social influence activity (i.e., the process of social influence wherein one person's attitudes and behaviors affect another's). To that end, we develop a novel model of network evolution where the dynamics of network follow the mechanism of influence propagation, which are not captured by the existing network evolution models. Our experiments confirm the predictions of our model and demonstrate the important role that social influence can play in the process of network evolution. As well exploring the reason of social network evolution, different genres of social influence have been spotted having different effects on the network dynamics. These findings and methods are essential to both our understanding of the mechanisms that drive network evolution and our knowledge of the role of social influence in shaping the network structure.
Over the past 5 years, on behalf of state governments, nearly 100,000 Americans were gently manipulated by a team of social scientists. In 15 randomized, controlled trials, people in need of social services either encountered the standard application process or received a psychological nudge, in which the information was presented slightly differently—a postcard reminded them of deadlines, for example, or one choice was made easier than another. In 11 of the trials, the nudge modestly increased a person’s response rate or influenced them to make financially smarter choices. The results, to be presented tomorrow at the annual meeting of the Association for Psychological Science in Chicago, Illinois, add to the growing evidence that nudges developed by psychologists can make a real difference in the success of government programs. “These interventions have positive effects,” says Sim Sitkin, director of the Behavioral Science & Policy Center at Duke University in Durham, North Carolina, who was not involved with the nudge trials. “They should be applied now.”
Attitudes toward risk ináuence the decision to diversify among uncertain options. Yet, because in most situations the options are ambiguous, attitudes toward ambiguity may also play an important role. I conduct a laboratory experiment to investigate the e§ect of ambiguity on the decision to diversify. I Önd that diversiÖcation is more prevalent and more persistent under ambiguity than under risk. Moreover, excess diversiÖcation under ambiguity is driven by participants who stick with a status quo gamble when diversiÖcation among gambles is not feasible. This behavioral pattern cannot be accommodated by major theories of choice under ambiguity.
Impact of Assumptions in Economic Analysis on Policy
This presentation examines the impact of economic assumptions on policy decisions. Economic analysis of targets for sustainable buildings by the Queensland Competition Authority (QCA) and the Rainwater Harvesting Association of Australia (RHAA) is examined as a case study. Contested points include which costs and benefits are inside or outside the boundaries of legitimate and recognised consideration. This presentation refers to those differences as boundary conditions and considers how these assumptions affect the outcome of analysis and government policy. Setting of boundary conditions (what was included, what was excluded and assumptions) in engineering and economic analysis dominates outcomes of decisions about government policy. The investigations outlined in this paper were combined to create an enhanced version of a systems analysis of a policy for setting targets for water savings on all new dwellings. It was established, using appropriate boundary conditions, that a 40% target for water savings is feasible for South East Queensland and provides a cost-benefit ratio of 2.1. These results indicate that a policy of mandating targets for sustainable buildings would provide substantial benefits to the state of Queensland, water utilities and citizens.
Abstract The present research examines the prevalence of predictions in daily life. Specifically we examine whether spending predictions for specific purchases occur spontaneously in life outside of a laboratory setting. Across community samples and student samples, overall self-report and diary reports, three studies suggest that people make spending predictions for about two-thirds of purchases in everyday life. In addition, we examine factors that increase the likelihood of spending predictions: the size of purchase, payment form, time pressure, personality variables, and purchase decisions. Spending predictions were more likely for larger, more exceptional purchases and for item and project predictions rather than time periods.
LOSS AVERSION AND RISK AVERSION ARE CORRELATED (AT LEAST WITH OUR TECHNIQUE) rala A student recently emailed us asking for some data from our 2008 paper: Goldstein, Daniel G., Johnson, Eric J. & Sharpe, William F. (2008). Choosing outcomes versus choosing products: Consumer-focused retirement investment advice. Journal of Consumer Research, 35(3), 440-456. In particular, they were interested in the correlation between estimates of risk aversion and loss aversion within a person, which can be seen in the above plot (Figure 4 in the article). We thought, why not make the data open to the whole world. Here they are: Goldstein, Johnson, Sharpe (2008) Loss Aversion and Risk Aversion Data subject: An anonymous identifier indexing the unique human who submitted the data dist: participants submitted two distributions (one right after another) in Year 1. They were invited back in Year 2 to submit distributions again. There was some dropout. This column tells you which distribution you are looking at. riskAversion: this is the coefficient of relative risk aversion, commonly referred to as alpha lossAversion: this is the coefficient of loss aversion, commonly referred to as lambda
This paper studies, theoretically and empirically, the role of overconfidence in political behavior. Our model of overconfidence in beliefs predicts that overconfidence leads to ideological extremeness, increased voter turnout, and stronger partisan identification. The model also makes nuanced predictions about the patterns of ideology in society. These predictions are tested using unique data that measure the overconfidence and standard political characteristics of a nationwide sample of over 3,000 adults. Our numerous predictions find strong support in these data. In particular, we document that overconfidence is a substantively and statistically important predictor of ideological extremeness, voter turnout, and partisan identification.
Psychologists and investment professionals have now identified over 100 separate biases, heuristics and cognitive quirks that cause us to make poor financial decisions. While this work is important, it is also unwieldy for the average investor who has a basic notion that behavior matters but is unable to track and protect against such a broad universe of potential error. Understanding that these 100+ errors are all undergird by a few common psychological tendencies, Nocturne Capital created this Behavioral Risk Taxonomy. The 5 general themes here encompass all of the individual errors but also provide a simple framework from which advisory and investment processes can be constructed that seek to overcome these tendencies. The ideas presented in the document linked below were instrumental in designing our investment process and we hope they are similarly instructive in your own efforts at compounding meaningful wealth. Behavioral Risk Taxonomy
Abstract: The study of brain dynamics currently utilizes the new features of nanobiotechnology and bioengineering. New geometric and analytical approaches appear very promising in all scientific areas, particularly in the study of brain processes. Efforts to engage in deep comprehension lead to a change in the inner brain parameters, in order to mimic the external transformation by the proper use of sensors and effectors. This paper highlights some crossing research areas of natural computing, nanotechnology, and brain modeling and considers two interesting theoretical approaches related to brain dynamics: (a) the memory in neural network, not as a passive element for storing information, but integrated in the neural parameters as synaptic conductances; and (b) a new transport model based on analytical expressions of the most important transport parameters, which works from sub-pico-level to macro-level, able both to understand existing data and to give new predictions. Complex biological systems are highly dependent on the context, which suggests a “more nature-oriented” computational philosophy. Nano-Modeling and Computation in Bio and Brain Dynamics. Available from: https://www.researchgate.net/publication/299566104_Nano-Modeling_and_Computation_in_Bio_and_Brain_Dynamics [accessed Apr 3, 2016].
Acts of terror promote economic uncertainty and financial anxiety in people, who instinctively react by reducing spending. A mere 5 percent reduction in personal consumption brought by fear of terrorism is enough to push the U.S. economy into the next recession by lowering Gross Domestic Product (GDP) by 3.5 percent. Acts of terror promote economic uncertainty and financial anxiety in people, who instinctively react by reducing spending. A 5 percent reduction in personal consumption, which makes up nearly 70 percent of the U.S. economy, will decrease Gross Domestic Product (GDP) by 3.5 percent or negative 1.4 percent based on the 2015 third quarter GDP of 2.1 percent. Terrorism impacts the economy in two distinct ways. The first is the immediate impact on commerce right after a terror attack. The November 2015 terror attack in Paris de facto paralyzed commerce in parts of Paris, and later on in the entire city of Brussels in Belgium, for a few days. Repeated economic disruptions like these can have severe economic impact on local and national economies.
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