Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

© Peter C. R. Lane, Fernand Gobet. This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY-NC 3.0)Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the ‘speciated non-dominated sorting genetic algorithm’ for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.Peer reviewedFinal Published versio

Open by Degrees: A Case of Flexibility or Personalization?

This chapter focuses on the history, development, and perceived value of The Open University UK’s BA/BSc (Hons) Open degree (hereafter referred to as “OUUK Open degree”) over the past half-century in the context of changing external pressures and addressing debates around the coherence and acceptance of such a personalized program of study. It touches on the changing views of “openness” over time, from the origins of The Open University’s “open entry” policy, through to ideas around flexibility of study, open education, and personalized learning. The chapter concludes with recommendations for other higher education institutions wishing to introduce a multidisciplinary open degree into their portfolio of curriculum

Normative values for the profile of mood states for use with athletic samples

The Profile of Mood States (POMS) has been used extensively for the assessment of mood in the sport and exercise environments. The purpose of the study was to develop tables of normative values based on athletic samples. Participants (N = 2,086), comprising athletes at the international (n = 622), club (n = 628), and recreational (n = 836) levels, completed the POMS in one of three situations: pre-competition/exercise, post-competition/exercise, and away from the athletic environment. Differences between the athletic sample and existing norms were found for all mood subscales. Main effects of level of competition and situation were identified. The results support the proposition that the use of the original tables of normative values in sport and exercise environments is inappropriate

Can government policies increase national long-run growth rates?

We obtain time series estimates of the long run growth rates of 17 OECD countries, and test the hypothesis that these are the same across countries. We find that we cannot reject this hypothesis for the first and last three decades of the 20th century. We conclude that: (i) there are few, if any, feasible policies available that have a significant effect on long run growth rates, and; (ii) any policies that can raise national growth rates must be international in scope. The results therefore have bleak implications for the ability of countries to affect their long run growth rates.economic policy, technological change, convergence, economic growth

WWII and Long Run Convergence in the OECD

Existing evidence for unconditional convergence in the OECD is mixed, and depends largely on whether time series or cross sectional methods are used. In this paper we reconsider the evidence for unconditional convergence by dividing the long run data into several subperiods. We use a two stage approach in this work. We first model the growth rate of output directly and use this model to estimate the long-run growth rate for the countries in our sample. We then use the estimates of long-run growth in output to test for unconditional convergence and to test for equality of long-run growth across countries. GLS is used to explicitly take into account the sampling uncertainty inherent in our estimates of the long-run growth rate we found in the first stage of the process. The results show strong evidence for unconditional convergence in the post WWII period 1951-1974, but no evidence of convergence in the periods preceding or following this period. Moreover, it is di±cult to reject the hypothesis that most of the countries in our sample had the same growth rate outside of this period. Thus find little evidence to suggest that absolute convergence has been a continuous long run process, and some evidence for the view that national policies mainly affect income levels rather than growth rateGrowth, Convergence, Technological Change

Re-evaluation of the factorial validity of the Revised Competitive State Anxiety Inventory-2

Anxiety is one of the most frequently researched constructs in the field of sport and exercise psychology. Although there are at least 22 published scales available to measure anxiety (see Ostrow, 1996), the Competitive State Anxiety Inventory-2 (CSAI-2: Martens, Burton, Vealey, Bump, & Smith, 1990) has generally been the scale of choice since its development. Given its prominence as a research tool, indeed it was described by Woodman and Hardy (2003, p.453) as having 'near sine qua non status', the CSAI-2 has naturally been the subject of considerable scrutiny of its psychometric characteristics. Several studies have now been published which have raised concerns about the factorial validity of the CSAI-2 in its English (Cox, Martens, & Russell, 2003; Lane, Sewell, Terry, Bartram, & Nesti, 1999), Greek (Tsorbatzoudis, Varkoukis, Kaissidis-Rodafinos, & Grouios, 1998), and Swedish (Lundqvist & Hassmen, in press) versions. Collectively, reevaluations of its psychometric properties have raised serious doubts about the validity of the CSAI-2 in its original form and by implication have cast a shadow over the findings of dozens of studies that have used it to measure anxiety. To address this situation, Cox et al. (2003) conducted a two-stage process using calibration and validation samples to arrive at an improved measure. Having deleted problematic items in the original CSAI-2 and having subsequently supported the factorial validity of a revised version of the measure, termed the CSAI-2R, they recommended that researchers and clinicians should in future use the revised measure in preference to the original. The purpose of the present study was to re-evaluate the factorial validity of the CSAI-2R, as recommended by Cox and colleagues. Considering the potential for the revised measure to become the new scale of choice for researchers in the sport and exercise domains, this is judged to be an important contribution to the anxiety literature