Using Simulation to Understand and Respond to Real World and Cyber Crises

2021 ◽  
pp. 111-127
Author(s):  
Jeremy Straub
Keyword(s):  
Case Studies ◽  
Real World ◽  
Optimal Decision ◽  
Limited Information ◽  
The Real ◽  
Crisis Situations

Crisis situations require decisions to be made rapidly and under higher pressure than under normal circumstances. In many cases, not all of the information required to make an optimal decision will be readily available, meaning decisions will need to be made with limited information or as information is being collected. This chapter considers how simulation can be used to prepare for and respond to crisis situations, both in the real world and in the cyber realm. To this end, prior uses of simulations are reviewed. Then a paradigm for the use of simulation to prepare for and respond to real-world and cyber crises is proposed and evaluated using four case studies. From this, general conclusions are drawn, and areas for additional study are identified.

Applying the Systems Evaluation Protocol in the real world: Six case studies

2021 ◽  
Vol 2021 (169) ◽  
pp. 65-77
Author(s):  
Jennifer Brown Urban ◽  
Miriam R. Linver ◽  
Lisa M. Chauveron ◽  
Thomas Archibald ◽  
Monica Hargraves ◽  
...  
Keyword(s):  
Case Studies ◽  
Real World ◽  
The Real ◽  
Evaluation Protocol

scholarly journals How to train your robot with deep reinforcement learning: lessons we have learned

2021 ◽  
pp. 027836492098785
Author(s):  
Julian Ibarz ◽  
Jie Tan ◽  
Chelsea Finn ◽  
Mrinal Kalakrishnan ◽  
Peter Pastor ◽  
...  
Keyword(s):  
Machine Learning ◽  
Reinforcement Learning ◽  
Case Studies ◽  
Real World ◽  
Review Article ◽  
The Real ◽  
Complex Skills ◽  
Real World Learning ◽  
Level Sensor ◽  
Embodied Agent

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.

scholarly journals Undergraduates Writing Publishable Cases: The Trials, The Tribulations, And The Real-World Learning

2011 ◽  
Vol 4 (12) ◽  
Author(s):  
Jason Smith ◽  
Josh Edwards ◽  
Patricia C. Kelley
Keyword(s):  
Case Studies ◽  
Real World ◽  
The Real ◽  
Real World Learning ◽  
Case Writing

If given the chance, undergraduates have the ability to write excellent case studies worthy of being published.  This essay describes the benefits, challenges, and process of undergraduate case writing. 

Contracts in the real world: Case studies from Southern Africa

2005 ◽  
Vol 60 (11) ◽  
pp. 2505-2514 ◽  
Author(s):  
Natasha Palmer ◽  
Anne Mills
Keyword(s):  
Case Studies ◽  
Southern Africa ◽  
Real World ◽  
The Real

scholarly journals Transformative mindfulness: the role of mind-body practices in community-based activism

2020 ◽  
pp. 147447402091888
Author(s):  
Benedikt Schmid ◽  
Gerald Taylor Aiken
Keyword(s):  
Social Change ◽  
Case Studies ◽  
Real World ◽  
The Political ◽  
Social Entrepreneurs ◽  
Community Based ◽  
The Real ◽  
Simple Observation ◽  
Body Practices

This article emerges from the simple observation that community-based social and environmental activists often engage with practices of mindfulness, either personally or collectively. It draws on two case studies, a UK-based Transition initiative and a community of social entrepreneurs in Germany. On the surface, social and environmental activists, committed to change in the ‘real world’, outward facing and public, jar with practices of ‘mindfulness’: personal and interior actions –‘private’. We argue that post-foundationalist understandings of community, particularly Nancy’s being-in-common – popularised within geography as ‘community economies’ – and the philosophical and spiritual roots of mindfulness are two lines of thought that provide clues to this co-occurrence. Going beyond understandings of collectivity that build on the coming together of preformed individuals or presuppose a common substance, we set the (Westernised) Buddhist influences on mindfulness, specifically the notion of interbeing, side by side with Nancy’s being-in-common. This article argues that both the political and spiritual aspects of activism are integral parts of social change. It concludes that post-foundational and Buddhist-inspired lines of thought cross-fertilise and chart a course towards transformative mindfulness.

How the P* Model Rationalizes Monetary Targeting: A Comment on Svensson

2001 ◽  
Vol 2 (3) ◽  
pp. 303-308 ◽  
Author(s):  
Franz Seitz ◽  
Karl-Heinz Tödter
Keyword(s):  
Real World ◽  
Special Form ◽  
Money Growth ◽  
Full Information ◽  
Limited Information ◽  
The Real ◽  
Monetary Targeting ◽  
Information Set

Abstract In this comment, we answer the question posed in Svensson's (2000) paper `Does the P* Model Provide any Rationale for Monetary Targeting?' - in contrast to him - in the affirmative. We argue that a strategy of monetary targeting can be rationalized within the P* framework. Furthermore, we demonstrate that money growth targeting is a special form of inflation forecast targeting based on a `limited' information set. In contrast to `full information' inflation forecast targeting, monetary growth targeting is likely to be more robust under changing conditions of the real world.

Panel discussion: applications in the real world: case studies in defining boundaries and managing innovation

2007 ◽  
Vol 74 (Suppl_2) ◽  
pp. S51-S59
Author(s):  
C. R. ADKISON ◽  
M. J. MEEHAN ◽  
G. H. CASSELL ◽  
J. P. KAHN ◽  
P. A. PIZZO ◽  
...  
Keyword(s):  
Case Studies ◽  
Real World ◽  
Panel Discussion ◽  
The Real ◽  
Managing Innovation
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