Memory and complex skills

Author(s):  
Malcolm Cook
Keyword(s):  
2003 ◽  
Author(s):  
Eric Anthony Day ◽  
Leigh E. Paulus ◽  
Winfred Arthur ◽  
Erich C. Fein

2020 ◽  
Vol 87 (6) ◽  
pp. 2542-2567
Author(s):  
B Biais ◽  
A Landier

Abstract While potentially more productive, more complex tasks generate larger agency rents. Agents therefore prefer to acquire complex skills, to earn large rents. In our overlapping generations model, their ability to do so is kept in check by competition with predecessors. Old agents, however, are imperfect substitutes for young ones, because the latter are easier to incentivize, thanks to longer horizons. This reduces competition between generations, enabling young managers to go for larger complexity than their predecessors. Consequently, equilibrium complexity and rents gradually increase beyond what is optimal for the principal and for society.


2021 ◽  
pp. 027836492098785
Author(s):  
Julian Ibarz ◽  
Jie Tan ◽  
Chelsea Finn ◽  
Mrinal Kalakrishnan ◽  
Peter Pastor ◽  
...  

Deep reinforcement learning (RL) has emerged as a promising approach for autonomously acquiring complex behaviors from low-level sensor observations. Although a large portion of deep RL research has focused on applications in video games and simulated control, which does not connect with the constraints of learning in real environments, deep RL has also demonstrated promise in enabling physical robots to learn complex skills in the real world. At the same time, real-world robotics provides an appealing domain for evaluating such algorithms, as it connects directly to how humans learn: as an embodied agent in the real world. Learning to perceive and move in the real world presents numerous challenges, some of which are easier to address than others, and some of which are often not considered in RL research that focuses only on simulated domains. In this review article, we present a number of case studies involving robotic deep RL. Building off of these case studies, we discuss commonly perceived challenges in deep RL and how they have been addressed in these works. We also provide an overview of other outstanding challenges, many of which are unique to the real-world robotics setting and are not often the focus of mainstream RL research. Our goal is to provide a resource both for roboticists and machine learning researchers who are interested in furthering the progress of deep RL in the real world.


2009 ◽  
Vol 11 (3) ◽  
pp. 366-376 ◽  
Author(s):  
Rebecca Wright ◽  
Belinda L. Guadagno ◽  
Martine B. Powell

The current study extends debate and research on the important role of practice in promoting and sustaining complex skills in investigative interviewing. Specifically, we explored the use of self-initiated practice as one avenue for facilitating ongoing development of professionals who interview children about abuse. A group of 40 investigative interviewers were required to organise and administer their own practice opportunities and to document these sessions in a diary. The professionals were aware of the important role of practice and what constitutes best-practice interview guidelines; however no instruction was given about the desired format, structure and timing of the practice sessions. A combination of quantitative and qualitative analyses revealed poor adherence to self-initiated practice, and the practice (among those who adhered to this model) had negligible impact on performance. Overall, these findings highlight the need for careful monitoring and evaluation of all interviewer practice tasks.


2010 ◽  
Vol 27 (3) ◽  
pp. 335-353 ◽  
Author(s):  
Sara Cushing Weigle

Automated scoring has the potential to dramatically reduce the time and costs associated with the assessment of complex skills such as writing, but its use must be validated against a variety of criteria for it to be accepted by test users and stakeholders. This study approaches validity by comparing human and automated scores on responses to TOEFL® iBT Independent writing tasks with several non-test indicators of writing ability: student self-assessment, instructor assessment, and independent ratings of non-test writing samples. Automated scores were produced using e-rater ®, developed by Educational Testing Service (ETS). Correlations between both human and e-rater scores and non-test indicators were moderate but consistent, providing criterion-related validity evidence for the use of e-rater along with human scores. The implications of the findings for the validity of automated scores are discussed.


2019 ◽  
Author(s):  
Motonori Yamaguchi

The need of typewriting skill is ever increasing in our lives. The prevalence of personal computers and mobile devices has transformed the way people communicate with each other. Although many different types of human interfaces have been introduced over the decades, the dominant form of computer interface remains to be that of typing on a keyboard. [...] Whilst typing has become one of the common everyday skills within the last two decades, experimental psychologists have been studying it as a research subject for more than a hundred years. [...] Apart from its practical importance in the modern lifestyle, the act of typing involves the right amount of complexity as well as well-defined and measurable actions. These features of typewriting makes it an ideal testbed to gain our understanding of the control and acquisition of complex skills. This review article first presents a brief overview of the classic studies of typewriting skill in the early 20th century, discusses the developments that took place after the mid-20th century, and concludes with the current status and issues that remain for future investigations in the 21st century.


1981 ◽  
Vol 18 (3) ◽  
pp. 363-379 ◽  
Author(s):  
Geoffrey W. Beeson

A total of 188 10th-grade students were taught a hierarchy of intellectual skills in one of three different contexts: one in which the skills were taught in isolation, one in which additional verbal instructions were provided, and a third in which the skills were taught in relation to a relevant anchoring idea. The students were tested following intervals of approximately 2 days and 7 weeks for achievement of the final task of the hierarchy, lateral transfer, and achievement of subordinate skills. With some qualifications, results supported the prediction that use of the anchoring idea context would enhance the meaningful learning and retention of the most complex skills.


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