Agent‐based computational models and generative social science

This article argues that the agent‐based computational model permits a distinctive approach to social science for which the term “generative” is suitable. In defending this terminology, features distinguishing the approach from both “inductive” and “deductive” science are given. Then, the following specific contributions to social science are discussed: The agent‐based computational model is a new tool for empirical research. It offers a natural environment for the study of connectionist phenomena in social science. Agent‐based modeling provides a powerful way to address certain enduring—and especially interdisciplinary—questions. It allows one to subject certain core theories—such as neoclassical microeconomics—to important types of stress (e.g., the effect of evolving preferences). It permits one to study how rules of individual behavior give rise—or “map up”—to macroscopic regularities and organizations. In turn, one can employ laboratory behavioral research findings to select among competing agent‐based (“bottom up”) models. The agent‐based approach may well have the important effect of decoupling individual rationality from macroscopic equilibrium and of separating decision science from social science more generally. Agent‐based modeling offers powerful new forms of hybrid theoretical‐computational work; these are particularly relevant to the study of non‐equilibrium systems. The agent‐based approach invites the interpretation of society as a distributed computational device, and in turn the interpretation of social dynamics as a type of computation. This interpretation raises important foundational issues in social science—some related to intractability, and some to undecidability proper. Finally, since “emergence” figures prominently in this literature, I take up the connection between agent‐based modeling and classical emergentism, criticizing the latter and arguing that the two are incompatible. © 1999 John Wiley & Sons, Inc.     

Buzzwords on their way to a tipping‐point: A view from the blogosphere

“Buzzwords” are new words (i.e., neologisms) that enter the language and acquire great popularity as “fashion words.” To date, the dynamic aspect of buzzwords has not been the subject of a rigorous scientific analysis. In this study, we analyzed the appearance of buzzwords in the blogosphere and compared their dynamics to the one of nonpopular neologisms and well‐established words. It was found that the growth rate of buzzwords is exponential and higher than that of the blogosphere. Moreover, we have identified general early warning signals for an approaching tipping point in the dynamics of buzzwords indicating that as fashion words they are on their way to a tipping‐point of decline. The article presents these findings and others and concludes by presenting a model for studying the dynamics of new words entering the language. © 2010 Wiley Periodicals, Inc. Complexity 16: 58‐68, 2011     

Agent‐based model for economic impact of free software

This article describes the potential impact that free (i.e., open source) software can have on an existing commercial software market. A model for the software market is constructed in terms of autonomous agents, which represent the users, the companies, and the free software providers. The model specifies a reservation price for each user agent and develops a gradient learning strategy for revenue‐maximizing company agents. Simulations explore parameters such as the demand distribution, and the relative importance of market share, advertising and random effects in product visibility. Results from the case without free software show a prevalence of monopolies, which is consistent with other studies of high‐technology market economics. The effects of free software are not uniform, but are highly parameter dependent. A “capture region” is found in which free software eventually dominates the market. © 2003 Wiley Periodicals, Inc.     

Psychometric Re‐evaluation of the Image of Science and Scientists Scale (ISSS)

An enduring concern among science education researchers is the “swing away from science” ( Osborne. 2003 ). One of their central dilemmas is to identify—or construct—a valid outcome measure that could assess curricular effectiveness, and predict students' choices of science courses, university majors, or careers in science. Many instruments have been created and variably evaluated. The primary purpose of this paper was to re‐evaluate the psychometric properties of the Image of Science and Scientists Scale (ISSS) ( Krajkovich 1978 ). In the current study, confirmatory factor analysis (CFA) was used to examine the dimensionality of the 29‐item ISSS, which was administered to 531 middle school students in three San Antonio. Texas school districts at the beginning of the 2004–2005 school year. The results failed to confirm the presumed 1‐factor structure of the ISSS. but instead showed a 3‐factor structure with only marginal fit with the data, even after removal of 12 inadequate items. The three dimensions were “Positive Images of Scientists” (5 items). “Negative Images of Scientists” (9 items), and “Science Avocation” (3 items). The results do not support use of the original form of the ISSS for measuring “attitudes toward science,”“images of scientists. “or “scientific attitudes. “Shortening the scale from 29 to 17 items makes it more feasible to use in a classroom setting. Determining whether the three dimensions identified in our analysis. “Positive Images of Scientists. ““Negative Images of Scientists. “and “Science Avocation “contain useful assessments of middle school student impressions and attitudes will require independent investigation in other samples.     

POPULATION‐LEVEL ANALYSIS AND VALIDATION OF AN INDIVIDUAL‐BASED CUTTHROAT TROUT MODEL

ABSTRACT. An individual‐based model of stream trout is analyzed by testing its ability to reproduce patterns of population‐level behavior observed in real trout: (1) “self‐thinning,” a negative power relation between weight and abundance; (2) a “critical period” of density‐dependent mortality in young‐of‐the‐year; (3) high and age‐specific inter‐annual variability in abundance; (4) density dependence in growth; and (5) fewer large trout when pool habitat is eliminated. The trout model successfully reproduced these patterns and was useful for evaluating their theoretical basis. The model analyses produced new explanations for some field observations and indicated that some patterns are less general than field studies indicate. The model did not reproduce field‐observed patterns of population variability by age class, discrepancies potentially explained by site differences, predation mortality being more stochastic than the model assumes, or uncertainty in the field study's age estimates.     

Bernstein–Nikolskii and Plancherel–Polya inequalities in Lp ‐norms on non‐compact symmetric spaces

By using Bernstein‐type inequality we define analogs of spaces of entire functions of exponential type in L_p (X), 1 ≤ p ≤ ∞, where X is a symmetric space of non‐compact. We give estimates of L_p ‐norms, 1 ≤ p ≤ ∞, of such functions (the Nikolskii‐type inequalities) and also prove the L_p ‐Plancherel–Polya inequalities which imply that our functions of exponential type are uniquely determined by their inner products with certain countable sets of measures with compact supports and can be reconstructed from such sets of “measurements” in a stable way (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

An optimal family of exponentially accurate one‐bit Sigma‐Delta quantization schemes

Sigma‐delta modulation is a popular method for analog‐to‐digital conversion of bandlimited signals that employs coarse quantization coupled with oversampling. The standard mathematical model for the error analysis of the method measures the performance of a given scheme by the rate at which the associated reconstruction error decays as a function of the oversampling ratio λ. It was recently shown that exponential accuracy of the form O(2^−rλ) can be achieved by appropriate one‐bit sigma‐delta modulation schemes. By general information‐entropy arguments, r must be less than 1. The current best‐known value for r is approximately 0:088. The schemes that were designed to achieve this accuracy employ the “greedy” quantization rule coupled with feedback filters that fall into a class we call “minimally supported.” In this paper, we study the discrete minimization problem that corresponds to optimizing the error decay rate for this class of feedback filters. We solve a relaxed version of this problem exactly and provide explicit asymptotics of the solutions. From these relaxed solutions, we find asymptotically optimal solutions of the original problem, which improve the best‐known exponential error decay rate to r ≈ 0.102. Our method draws from the theory of orthogonal polynomials; in particular, it relates the optimal filters to the zero sets of Chebyshev polynomials of the second kind. © 2011 Wiley Periodicals, Inc.     

Inverse spectral problem of fourth‐order boundary value problems with finite spectrum

In the present paper, we consider a class of inverse spectral problem of fourth‐order boundary value problems. Under the so‐called “Atkinson type” conditions, the problem has finite spectrum and corresponding matrix representations. By using the method of inverse matrix eigenvalue problems of two‐banded matrix, the leading coefficient and potential functions are reconstructed from the given three sets of interlacing real numbers satisfying certain conditions.     

Development and Field Test of the Modified Draw‐a‐Scientist Test and the Draw‐a‐Scientist Rubric

Even long before children are able to verbalize which careers may be interesting to them, they collect and store ideas about scientists. For these reasons, asking children to draw a scientist has become an accepted method to provide a glimpse into how children represent and identify with those in the science fields. Years later, these representations may translate into students' career choices. Since 1995, children's illustrations of scientists have been assessed by the Draw‐a‐Scientist Checklist (DAST‐C). The checklist was created from the common aspects or features found in illustrations from previous studies and were based initially on the scientists, broken down into “stereotypical” and “alternative” images shown in the drawings. The purpose of this article is to describe the development, field test, and reliability of the modified DAST Test and the DAST Rubric designed as an improvement of the DAST‐C to provide a more appropriate method of assessing students' drawings of scientists. The combination of the modified DAST and the DAST Rubric brings more refinement as it enables clarities to emerge and subsequently increased detail to what one could ascertain from students about their mental images of scientists.     

On the Initial‐Boundary Value Problem for the Linearized Boussinesq Equation

This work is concerned with the initial‐boundary value problem for the Boussinesq equation. By employing the unified transform method of Fokas, novel solution formulae for the linearized “good” Boussinesq equation on the half‐line with various initial and boundary conditions are obtained. Moreover, these solution formulae are numerically illustrated in the case of concrete data. Finally, Boussinesq's original physical derivation of the so‐called “bad” Boussinesq equation is provided.     

CATCHMENT BEHAVIOR AND COUNTER‐CYCLICAL WATER TRADE: AN INTEGRATED MODEL

ABSTRACT. Murray Basin water resources are under increasing pressure to satisfy often conflicting environmental and economic objectives. Governments, as the “environmental steward,” have several management options including water trading and banking water until it can be used to greatest effect and occasionally selling water back to irrigators. This is sometimes known as counter‐cyclic trading. To examine the potential of the above options, a model of water trading and banking in a simple market is developed. The model combines a catchment hydrology model with economic information that drives land use practice and demand for water. Simulations are used to explore these options at a strategic level. The potential impacts of increased upland afforestation and climate change on catchment hydrology in the presence of a pro‐active environmental steward are considered. It is concluded that in a system where entitlements are capped it is likely that the most cost‐effective management system will involve counter‐cyclic trading.     

The Effects of Project‐Based Learning on Students' Academic Achievement,Attitude, and Retention of Knowledge: The Subject of “Electricity in Our Lives”

The aim of this study is to analyze the effects of project‐based learning on students' academic achievement, attitude, and retention of knowledge in relation to the subject of “Electricity in Our Lives” in a fourth‐grade science course. The study was conducted in a quasi‐experimental design as a “pre‐test, post‐test with control group.” In the experimental group, the unit was taught through the project‐based learning method. The measuring tools were administered to both groups before and after the applications. To perfectly analyze the “process” of the method, seven different learning assessment “forms” were administered to the students. The findings of the forms indicated that the students learn to construct their own learning and to evaluate changes in their own behavior through the application of the method. The application of different methods between both groups had a statistically significant effect in terms of academic achievement, (F(1,112) = 46.78, p = .000) and of retention of knowledge (F(1,112) = 35.24, p = .000). However, there were no statistically significant effects from being in different groups for the attitudes of students (F(1,112) = .99, p = .321). For the students, being in the project‐based learning groups resulted in better academic achievement and retention of knowledge than being in the traditional teaching group.     

On the structure of clique‐free graphs

Using a clever inductive counting argument Erd?s, Kleitman and Rothschild showed in 1976 that almost all triangle‐free graphs are bipartite, i.e., that the cardinality of the two graph classes is asymptotically equal. In this paper we investigate the structure of the “few” triangle‐free graphs which are not bipartite. As it turns out, with high probability, these graphs are bipartite up to a few vertices. More precisely, almost all of them can be made bipartite by removing just one vertex. Almost all others can be made bipartite by removing two vertices, and then three vertices and so on. We also show that similar results hold if we replace “triangle‐free” by K_??+1‐free and “bipartite” by ??‐partite. © 2001 John Wiley & Sons, Inc. Random Struct. Alg., 19, 37–53, 2001     

Artificial intelligence and social forecasting*

Artificial intelligence (AI) is the study of how to write programs enabling computers to do things that would require intelligence if done by people, and it could engage with social forecasting in two ways. First, it is part of the overall social‐technological context within which forecasters work. Commercial Al‐programs will affect markets and life‐styles; and advice‐giving “expert” systems will raise novel legal, social, and psychological problems. Second, AI‐programs might be used for making the social forecasts. Unlike the (essentially quantitative) computer models used for this purpose today, they could reason (and explain themselves) in verbal form. Writing an expert system requires clarification of the theories, assumptions, and “rule‐of‐thumb” inferences concerned. It would be easier to identify the inherent moral‐political bias than it is in models comprising sets of differential equations.     

Failure in Complex Social Networks

A class of inhomogenously wired networks called “scale-free” networks have been shown to be more robust against failure than more homogenously connected exponential networks. The robustness of scale-free networks consists in their ability to remain connected even when failure occurs. The diffusion of information and disease across a network only requires a single contact between nodes, making network connectivity the crucial determinant of whether or not these “simple contagions” will spread. However, for “complex contagions,” such as social movements, collective behaviors, and cultural and social norms, multiple reinforcing ties are needed to support the spread of a behavior diffusion. I show that scale-free networks are much less robust than exponential networks for the spread of complex contagions, which highlights the value of more homogenously distributed social networks for the robust transmission of collective behavior.     

Finite‐volume scheme for a degenerate cross‐diffusion model motivated from ion transport

An implicit Euler finite‐volume scheme for a degenerate cross‐diffusion system describing the ion transport through biological membranes is proposed. The strongly coupled equations for the ion concentrations include drift terms involving the electric potential, which is coupled to the concentrations through the Poisson equation. The cross‐diffusion system possesses a formal gradient‐flow structure revealing nonstandard degeneracies, which lead to considerable mathematical difficulties. The finite‐volume scheme is based on two‐point flux approximations with “double” upwind mobilities. The existence of solutions to the fully discrete scheme is proved. When the particles are not distinguishable and the dynamics is driven by cross diffusion only, it is shown that the scheme preserves the structure of the equations like nonnegativity, upper bounds, and entropy dissipation. The degeneracy is overcome by proving a new discrete Aubin–Lions lemma of “degenerate” type. Numerical simulations of a calcium‐selective ion channel in two space dimensions show that the scheme is efficient even in the general case of ion transport.     

Mathematics Teachers' Instructional Practices in an Era of High‐Stakes Testing

This study explored mathematics teachers' instructional practices in the context of high‐stakes testing. Data were obtained from a survey instrument given to a stratified sample of Mississippi and Tennessee teachers who teach the same content tested on their state's high school graduation examination. An analysis showed teachers using a balance of standards‐based and traditional practices and tools, including textbook‐based assignments, calculators, open‐response questions, supplementary materials, and multiple‐choice questions. Over 90% of teachers from both states felt that an “interest in helping my students attain test scores that will allow them to graduate high school” was a factor influencing their instructional practices. This was followed by an “interest in helping my school improve high school graduation examination scores,” and “belief these are the best instructional practices.”     

Relaxed stability conditions for continuous‐time Takagi–Sugeno fuzzy systems based on a new upper bound inequality

The important issue of reducing the conservatism of feasible stability criteria for continuous‐time Takagi–Sugeno fuzzy systems is studied in this article. In order to obtain more advanced result than previous ones, a new upper bound inequality is proposed and thus the properties of the normalized fuzzy weighting functions' time derivatives can be better used than the previous ones. In particular, the so‐called “redundant terms” considered in previous literature can be converted to “useful terms” which play a positive role in the underlying analysis process. Moreover, some useless additional variables and their derived inequalities are removed for enhancing the efficiency. Finally, an illustrative example is given to show the effectiveness of the proposed method. © 2016 Wiley Periodicals, Inc. Complexity 21: 289–295, 2016     

Students' Attitudes Toward Science as Predictors of Gains on Student Content Knowledge: Benefits of an After‐School Program

High‐quality after‐school programs devoted to science have the potential to enhance students' science knowledge and attitudes, which may impact their decisions about pursuing science‐related careers. Because of the unique nature of these informal learning environments, an understanding of the relationships among aspects of students' content knowledge acquisition and attitudes toward science may aid in the development of effective science‐related interventions. We investigated the impact of a semester‐long after‐school intervention utilizing an inquiry‐based infectious diseases curriculum (designed for use after‐school) on 63 urban students' content knowledge and aspects of their attitudes toward science. Content knowledge increased 24.6% from pretest to posttest. Multiple regression analyses indicated suggested that the “self‐directed effort” subscale of the Simpson–Troost Attitude Questionnaire—Revised best predicted increases in students' science content knowledge. The construct “science is fun for me” served as a suppressor effect. These findings suggest that future after‐school programs focusing on aspects of attitudes toward science most closely associated with gains in content knowledge might improve students' enthusiasm and academic preparedness for additional science coursework by improving student attitudes toward their perceptions of their self‐directed effort.     

A STATE‐SPACE MODEL FOR UNIVARIATE ORDINAL‐VALUED TIME SERIES

Abstract A state‐space model was developed to analyze a univariate time series of ordinal‐valued flower phenology data. Flower abundance, recorded as either “none,”“some,” or “much,” was observed each month on trees in a lowland Costa Rican rain forest to investigate flowering patterns of different species. Data from a single Capparis pittieri and daily rain measurements are used to demonstrate the model. A method to obtain maximum likelihood estimates of the parameters and the use of predicted probability differences to assess goodness of fit are described. Opportunities for improving the model are also discussed.