Nell'era della cybernetica e del web, che fanno da sfondo ad una crisi economica non circoscrivibile, è la neuroscienza la nuova frontiera della società globalizzata che conosciamo e che si sta trasformando. Lo studio del cervello umano e dei comportamenti degli individui attraverso tecniche di Imaging da Risonanza Magnetica (IRM) viene sperimentato da anni all'interno dei laboratori scientifici di un ristrettissimo numero di società nel mondo. Dietro progetti di ricerca per la cura contro cancro, parkinson o alzheimer, si nasconde un'attività di tracciamento e archiviazione delle immagini proiettate dal nostro cervello rispondendo a degli stimoli esterni, che permettono così di comprendere i meccanismi del subconscio umano, e quindi i meccanismi che sono alla base di una decisione razionale. L'IRM sottopone alle 'cavie' una serie di foto, video, odori, oggetti, cibo, per vedere quali aree del cervello vengono attivate. Gli scienziati specializzati nelle neuroscienze analizzano le interazioni tra queste aree che, avendo una diretta influenza sull'inconscio e sulla predeterminazione sociale, condizionano il comportamento dei consumatori e la loro coscienza. https://t.co/fusmjveV6Z
Research offers several proved strategies for boosting turnout on Election Day
TO VOTE OR NOT TO VOTE Although tackling political barriers to voting remains critical, the great strength of these behavioral interventions lies in their ability to overwhelm obstacles by catalyzing citizen motivation. And for people who do not vote because they believe one person's ballot cannot change election outcomes, behavioral science also offers a reason why voting is important for individuals. Research has found that in addition to signaling who we are to others, our actions tell us something about ourselves—shaping our own preferences and beliefs. From this perspective, people who do not vote are not merely abstaining from the democratic process in one instance. They are also “telling” themselves: “I don't care about politics.” Moving forward, they may also become less interested in civic rights, local governance, foreign affairs, and so on. And for those who do vote, participation is not just an expression of interest in current politics but also a seed that could grow into an active political life.
A herd of heuristic algorithms is compared using a portfolio optimization. Previously “A comparison of some heuristic optimization methods” used two
Previously “A comparison of some heuristic optimization methods” used two simple and tiny portfolio optimization problems to compare a number of optimization functions in the R language. This post expands upon that by using a portfolio optimization problem that is of a realistic size (but still with an unrealistic lack of constraints). Test case The optimization problem is to select 30 assets out of a universe of 474 and find their best weights. The weights must be non-negative and sum to 1. The integer constraint is binding — more than 30 assets in the portfolio can give a better utility. The utility is mean-variance. Each optimizer was run 100 times. To have a fair comparison the amount of time that each run took was controlled to be about 1 kilosecond. (There are a couple that also have runs that take much less time.) The timings are not all particularly close to 1000 seconds, but they are probably all close enough that the picture is minimally distorted.
“…e are suspicious of rapid cognition. We live in a world that assumes that the quality of a decision is directly related to the time and effort that went into...."
The FFTrees package contains lots of other functions for visualising and comparing trees. To see all the details, be sure to check out the package vignettes either in the package or on CRAN (here). For all you judgment and decision making researchers out there, I will also be presenting the package at the annual meeting of the Society for Judgment and Decision Making (SJDM) in Boston in November 2016 The package is also very much in development, so I am grateful for any recommendations, bug-reports, or criticisms. You can post bug-reports at www.github.com/ndphillips/FFTrees/Issues, or email me directly at Nathaniel.D.Phillips.firstname.lastname@example.org
Last week the Competition and Markets Authority (CMA) published the final report of their retail banking market investigation. The CMA has identified that currently, only a tiny proportion of customers switch to a different bank in any year; despite the fact that many of them could save about £90 a year by switching. A quarter of people in the UK use an unauthorised overdraft each year, suggesting they do not have the best account for them: this earns the banks £1.2 billion a year from unauthorised overdraft charges. The report proposed three foundation measures as the basis for their package of remedies. All three foundation measures have strong behavioural aspects: Requiring banks to implement Open Banking to help consumers share their data securely with other banks and third parties. This will help make it easier for consumers to shop around and compare banking products (making it easy). Requiring banks to prominently display a number of core indicators of service quality, including whether a personal customer or small business is willing to recommend their bank to friends, family and colleagues (making it attractive). Introducing routine and occasional prompts for personal and business customers to encourage them to consider their current banking arrangements and shop around for alternative banking services (making it timely). Those of you who have read our recent report on applying behavioural insights to regulated markets will recognise that these remedies strongly echo the principles set down in that paper: we will now set out their behavioural underpinning in a bit more detail.
Peer review is intended to act as a gatekeeper in science. If working researchers deem a paper fit to be published, it should mean that the research is sound, rigorous, and accurate. But an experimental analysis of peer review suggests that peer review might also end up rejecting high-quality material. The analysis points to high levels of competition as the source of the problem. Because peer review is a vastly complex system that can function quite differently in various disciplines, researchers Stefano Balietti, Robert L. Goldstone, and Dirk Helbing constructed an experimental game designed to mimic some of the primary features of peer review. Participants were divided into 16 groups of nine people each and tasked with creating a piece of “art” on a computer interface. The pieces could then be submitted to one of three “art exhibitions.” Each participant was then given three pieces of other people's art to review; pieces that averaged a score higher than five out of ten were accepted into the exhibition. Each group played 30 rounds of the game.
About the Course: In this course you'll gain an introduction to the modern study of dynamical systems, the interdisciplinary field of applied mathematics that studies systems that change over time. Topics to be covered include: phase space, bifurcations, chaos, the butterfly effect, strange attractors, and pattern formation. The course will focus on some of the realizations from the study of dynamical systems that are of particular relevance to complex systems: 1. Dynamical systems undergo bifurcations, where a small change in a system parameter such as the temperature or the harvest rate in a fishery leads to a large and qualitative change in the system's behavior. 2. Deterministic dynamical systems can behave randomly. This property, known as sensitive dependence or the butterfly effect, places strong limits on our ability to predict some phenomena. 3. Disordered behavior can be stable. Non-periodic systems with the butterfly effect can have stable average properties. So the average or statistical properties of a system can be predictable, even if its details are not. 4. Complex behavior can arise from simple rules. Simple dynamical systems do not necessarily lead to simple results. In particular, we will see that simple rules can produce patterns and structures of surprising complexity.
Abstract This article applies complexity theory to urban governance. It is argued that expert-based, hierarchical-instrumental policy making encounters insurmountable obstacles in modern liberal democracies. One of the root causes of this erosion of output legitimacy is the complexity of social systems. Complexity is defined as the density and dynamism of the interactions between the elements of a system. Complexity makes system outcomes unpredictable and hard to control and, for this reason, defies such well-known policy strategies as coordination from the center, model building, and reduction of the problem to a limited number of controllable variables. It is argued that participatory and deliberative models of governance are more effective in harnessing complexity because they increase interaction within systems and thereby system diversity and creativity. Using empirical data from research on citizen participation in disadvantaged neighborhoods in the Netherlands, the author shows (a) that neighborhoods can fruitfully be seen as complex social systems and (b) the different ways in which citizen participation is effective in harnessing this complexity.
Interview with David Byrne The following is a brief interview I conducted with British Sociologist and Complexity Scientist, David Byrne. Dr. Byrne is Professor in the School of Applied Social Sciences at Durham University, England, where he is also Director of Postgraduate Studies. Dr. Byrne is the author of several books and a long list of articles, including his 1998 book, Complexity Theory and the Social Sciences--the first book to critically review and explore the application of complexity science to sociological inquiry. His most recent book, edited with noted sociologist and methodologist, Charles Ragin is The SAGE Handbook of Case-Based Methods Dr. Byrne is an expert in methods, urban planning, community health, social policy, social exclusion and complexity science.
Abstract The social world is complex and emergent. Inquiry, directed towards establishing universal empirical regularities (i.e. nomothetic inquiry), cannot establish causality in such a world. We can never assign a causal effect to any intervention without assessing the whole context of that intervention. However, we can develop generalizable knowledge if we adopt research approaches that recognize both the implications of assigning causal powers to context (the essence of the realist take on evaluation) and the significance of human agency in relation to ‘the social type of causal nexus’. There are literatures that can contribute to developing such knowledge. These include macro-political science’s concern with the importance of temporal ordering in relation to outcomes; Ragin’s set theoretic understanding of causal relations and his development of systematic comparison as a basis for explicating those relations through Qualitative Comparative Analysis (QCA); and the presentation of causal narratives as foundation for process tracing. Every complex social intervention has to be considered as a ‘case’. Systematic comparison across cases allows us to generalize within limits – but this still means we can transfer knowledge beyond the unique ideographically described instance. We can never establish universal/nomothetic accounts of causality in complex systems by using variable-based methods such as Randomized Controlled Trials (RCTs). However, through careful comparison and exploration of complex contingent causation, we can begin to get a handle on what works where (in what context), when (in what temporal context), and in what order.
In this paper, we will put forward an original experiment to reveal empirical "anomalies" in the process of acquisition, elaboration and retrieval of information in the context of reading. We show that the acquisition and elaboration of information leads to the formation of a mental picture that may be incompatible with the information stored in memory. To answer some specific questions, individuals make use of a mental picture rather than combine their stored information appropriately. Our hypothesis is that quantum cognition theory provides a fruitful interpretative framework to account for these anomalies. Finally, we provide evidence that individuals with a low CRT (Cognitive Reflection Test) score tend to demonstrate, more often than not, this particular behavior. Keywords: quantum cognition, learning, experimental economics JEL: C91 C90 D83 C21 URL: http://d.repec.org/n?u=&r=cbe
Abstract: This encyclopedia entry discusses how the intersection of perennial legal questions and new neuroscientific advances has fueled the emergence of a new field: Law & Neuroscience. It provides an overview of issues, discussing both the promise and the limitations.
Behavior is the result of complexes mental processes that take place within our brain and it is clear that for the most we are not aware of such processes taking place, this implies a series of important considerations. The effects of these processes may produce a concrete impact on decisional processes that can influence dramatically the proceedings especially in high demand tasks and in specific professions. For example, we tend to believe to have control over the way we perceive the reality, we tend to overestimate the capability of memorizations of information. I will try to explain briefly a series of processes to highlight the limitation of human brain. We store information in our memory, what is working memory? Working memory is a cognitive system that maintains and elaborates information; it processes simultaneously both the incoming information and the retrieval of information. According to Baddeley, the working memory manipulates the information through three components: the phonological loop, the central executive and the visuospatial sketchpad. The visuospatial sketchpad (VS) holds visual and spatial information, this means that for example, the VS retains the information of how a word is written and where is spatially located but also is the place in which are retained and manipulated visual images. According to Shepard and Mezler, their experiment of comparing objects demonstrates how the VS is involved in the process of visual imagery; they presented four objects and asked to subjects to indicate whether these objects were the same or different objects, the subjects recognized the objects as being the same but rotated, this answer occurred in few second and they used the mental rotation function that is a function located within the visuospatial sketchpad’s function. https://www.linkedin.com/pulse/brief-introduction-cognitive-psychology-applied-paola-giannetakis
It just got a lot easier to simulate the performance of simple heuristics. The post Heuristica: An R package for testing models of binary choice appeared first
Here’s the heuristica package’s home on CRAN and here’s a description of the package in the authors’ own words: The heuristica R package implements heuristic decision models, such as Take The Best (TTB) and a unit-weighted linear model. The models are designed for two-alternative choice tasks, such as which of two schools has a higher drop-out rate. The package also wraps more well-known models like regression and logistic regression into the two-alternative choice framework so all these models can be assessed side-by-side. It provides functions to measure accuracy, such as an overall percentCorrect and, for advanced users, some confusion matrix functions. These measures can be applied in-sample or out-of-sample. The goal is to make it easy to explore the range of conditions in which simple heuristics are better than more complex models. Optimizing is not always better!
Homo Oeconomicus (HOEC) started life in 1983 as a German language occasional series concerned with various aspects of the theoretical and behavioral concept of homo economicus and its application in economics, philosophy, political science, and sociology. In 1995 it became a quarterly journal and in 1998 was fully internationalized with articles being exclusively in English. Since then Homo Oeconomicus has become an outlet for researchers working in the field of political economy, and a huge number of important papers have been published in the journal. From 2016 onward, Homo Oeconomicus is published by Springer. The journal will benefit from the modern technology and large distribution of an international publisher. We are proud to present the first issue of Homo Oeconomicus after its relaunch in early 2016.
“Behavioral economics" is still economics, but it is economics done with strong injections of good psychology and other social sciences.
Early in my teaching career I managed to inadvertently get most of the students in my microeconomics class mad at me, and for once, it had nothing to do with anything I said in class. The problem was caused by a midterm exam. I had composed an exam that was designed to distinguish among three broad groups of students: the stars who really mastered the material, the middle group who grasped the basic concepts, and the bottom group who just didn’t get it. To successfully accomplish this task, the exam had to have some questions that only the top students would get right, which meant that the exam was hard. The exam succeeded in my goal—there was a wide dispersion of scores—but when the students got their results they were in an uproar. Their principal complaint was that the average score was only 72 points out of a possible 100.
About the Course: This course will explore how to use agent-based modeling to understand and examine a widely diverse and disparate set of complex problems. During the course, we will explore why agent-based modeling is a powerful new way to understand complex systems, what kinds of systems are amenable to complex systems analysis, and how agent-based modeling has been used in the past to study everything from economics to biology to political science to business and management. We will also teach you how to build a model from the ground up and how to analyze and understand the results of a model using the NetLogo programming language, which is developed and supported at Northwestern University by Uri Wilensky. We will also discuss how to build models that are sound and rigorous. No programming background or knowledge is required, and the methods examined will be useable in any number of different fields. While this course is in session, the first unit will be completely free and open; we request a modest tuition to continue through the course and to receive a certificate. Once the course is closed, the videos and quizzes will all be open and freely available. A limited number of scholarships are available, please see the FAQ for more details.
It is of societal importance to advance the understanding of emerging patterns of biodiversity from biological and ecological systems. The neutral theory offers a statistical-mechanical framework that relates key biological properties at the individual scale with macroecological properties at the community scale. This article surveys the quantitative aspects of neutral theory and its extensions for physicists who are interested in what important problems remain unresolved for studying ecological systems.
How the Brain Makes Blame and Punishment Decisions . New work by researchers at Vanderbilt University and Harvard University confirms that a specific area of the brain, the dorsolateral prefrontal cortex, is crucial to punishment decisions. Researchers predicted and found that by altering brain activity in that region of the brain they could not only change how much subjects punished hypothetical defendants, bu
John H. Holland's general theories of adaptive processes apply across biological, cognitive, social, and computational systems.In August 2015, Professor John H. Holland passed away in Ann Arbor, MI, where he had served on the University of Michigan faculty for more than 50 years. John, as he was known universally to his colleagues and students, leaves behind a long legacy of intellectual achievements. As a descendant of the cybernetics era, he was influenced by the work of John von Neumann, Norbert Wiener, W. Ross Ashby, and Alan Turing, all of whom viewed computation as a broad, interdisciplinary enterprise. Holland thus became an early proponent of interdisciplinary approaches to computer science and an active evangelist of what is now called computational thinking, reaching out enthusiastically to psychologists, economists, physicists, linguists, philosophers, and pretty much anyone he came in contact with. As a result, even though he received what was arguably one of the world's first computer science Ph.D. degrees in 1959,23 his contributions are sometimes better known outside computer science than within. Holland is best known for his invention of genetic algorithms (GAs), a family of search and optimization methods inspired by biological evolution. Since their invention in the 1960s, GAs have inspired many related methods and led to the thriving field of evolutionary computation, with widespread scientific and commercial applications. Although the mechanisms and applications of GAs are well known, they were only one offshoot of Holland's broader motivation—to develop a general theory of adaptation in complex systems. Here, we consider this larger framework, sketching the recurring themes that were central to Holland's theory of adaptive systems: discovery and dynamics in adaptive search; internal models and prediction; exploratory modeling; and universal properties of complex adaptive systems.
Dear Behavioral Economics group members I'm pleased to announce that Elsevier is launching a new book series, 'Perspectives on Behavioral Economics and the Economics of Behavior', led by Editor-in-Chief Morris Altman. This series will be a platform for the dissemination and development of frontier research in behavioral economics, emphasizing empirical application, institutional and social context, empirically informed models, and multi-disciplinary perspectives. It aims to encourage and disseminate exemplary interdisciplinary research which demonstrates how economic and socio-economic behavior emerges from psychological, institutional, and social antecedents, and goes on to influence the real-world economy. Focusing particularly on modern problems and emergent research in behavioral economics, the series covers institutional design, governance, nudging, market inefficiencies, heuristics and decision-making, preference formation, framing, causality versus correlation in model building, loss aversion, herding, emotions and decision-making, as well as the importance of trust, altruism, and fairness in decision-making. It takes account of traditional economic models but seeks to advance the field by integrating perspectives from other fields, including experimental economics, economic psychology, neuroscience, and more broadly from the social sciences, particularly sociology, political science and law. As part of the launch activities for the books series, we are now searching for appropriately qualified researchers and practitioners interested in writing or editing new books on attractive aspects of behavioral research in economics. I'd be delighted to speak with you if you may have an interest in contributing a volume, or would like to know more. Please just reply privately to this message if so. Thanks for your time,
As you sit reading this, you probably experience an internal voice, unheard by any outsider, that verbally repeats the words you see on the page. That voice (which, in your case, speaks perfect English) is part of what we call your conscious mind. And the physical organ that causes what you see on the page …
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