Business Commons^™

Neural-Progressive Hedging: Enforcing Constraints In Reinforcement Learning With Stochastic Programming, Supriyo Ghosh, Laura Wynter, Shiau Hong Lim, Duc Thien Nguyen

Research Collection School Of Computing and Information Systems

We propose a framework, called neural-progressive hedging (NP), that leverages stochastic programming during the online phase of executing a reinforcement learning (RL) policy. The goal is to ensure feasibility with respect to constraints and risk-based objectives such as conditional value-at-risk (CVaR) during the execution of the policy, using probabilistic models of the state transitions to guide policy adjustments. The framework is particularly amenable to the class of sequential resource allocation problems since feasibility with respect to typical resource constraints cannot be enforced in a scalable manner. The NP framework provides an alternative that adds modest overhead during the online phase. …

Cybersecurity Risk Assessment Using Graph Theoretical Anomaly Detection And Machine Learning, Goksel Kucukkaya

Engineering Management & Systems Engineering Theses & Dissertations

The cyber domain is a great business enabler providing many types of enterprises new opportunities such as scaling up services, obtaining customer insights, identifying end-user profiles, sharing data, and expanding to new communities. However, the cyber domain also comes with its own set of risks. Cybersecurity risk assessment helps enterprises explore these new opportunities and, at the same time, proportionately manage the risks by establishing cyber situational awareness and identifying potential consequences. Anomaly detection is a mechanism to enable situational awareness in the cyber domain. However, anomaly detection also requires one of the most extensive sets of data and features …

Deploying Machine Learning For A Sustainable Future, Cary Coglianese

All Faculty Scholarship

To meet the environmental challenges of a warming planet and an increasingly complex, high tech economy, government must become smarter about how it makes policies and deploys its limited resources. It specifically needs to build a robust capacity to analyze large volumes of environmental and economic data by using machine-learning algorithms to improve regulatory oversight, monitoring, and decision-making. Three challenges can be expected to drive the need for algorithmic environmental governance: more problems, less funding, and growing public demands. This paper explains why algorithmic governance will prove pivotal in meeting these challenges, but it also presents four likely obstacles that …

Return On Investment Of The Cftp Framework With And Without Risk Assessment, Anne Lim Lee

Walden Dissertations and Doctoral Studies

In recent years, numerous high tech companies have developed and used technology roadmaps when making their investment decisions. Jay Paap has proposed the Customer Focused Technology Planning (CFTP) framework to draw future technology roadmaps. However, the CFTP framework does not include risk assessment as a critical factor in decision making. The problem addressed in this quantitative study was that high tech companies are either losing money or getting a much smaller than expected return on investment when making technology investment decisions. The purpose of this research was to determine the relationship between returns on investment before and after adding risk …

An Appraisal Of The Actuaries’ Climate Risk Index, Stephen Lee Kolk

May 18, 2016: The Economic Impacts of Sea-Level Rise in Hampton Roads

PDF of powerpoint presentation given at the workshop "The Economic Impacts of Sea-Level Rise in Hampton Roads: An Appraisal of the Projects Underway" on May 18, 2016 at the Virginia Modeling and Simulation Center, 1030 University Blvd, Suffolk, VA 23435

Judging Dread: A Quantitative Investigation Of Affect, Psychometric Dread And Risk Consequence, Melvyn Griffiths

Theses: Doctorates and Masters

Risk is generally understood as a product of the likelihood and consequence of an event. However, the way in which estimations of consequences are formed is unclear due to the complexities of human perception. In particular, the influence of Affect, defined as positive or negative qualities subjectively assigned to stimuli, may skew risk consequence judgements. Thus a clearer understanding of the role of Affect in risk consequence estimations has significant implications for risk management, risk communication and policy formulation.

In the Psychometric tradition of risk perception, Affect has become almost synonymous with the concept of Dread, despite Dread being measured …

Issue Brief: Saving By Mitigating, University Of Louisville, New England Environmental Finance Center

Sustainable Communities Capacity Building

Natural disasters can cause loss of life, inflict damage to buildings and infrastructure, and have devastating consequences for a community’s economic, social, and environmental well-being. Hazard mitigation means reducing damages from disasters.

Local governments have the responsibility to protect the health, safety, and welfare of their citizens. Proactive mitigation policies and actions help reduce risk and create safer, more disaster-resilient communities. Mitigation is an investment in your community’s future safety, equity, and sustainability.

Slides: Hydrofracking: Air Issues And Community Exposure, Debra A. Kaden

Air Quality Impacts from Oil and Gas Development (January 27)

Presenter: Debra Kaden, Ph.D., Toxicologist, ENVIRON International Corporation, discusses air concentrations of chemicals of potential health concern surrounding oil and gas development activities, as well as temporal and spatial patterns of these chemicals in the ambient environment. Such information is necessary to evaluate possible health impacts of the drilling process on air in surrounding communities.

19 slides

Final Technical Report For Grant De-Fg01-96ew56093 Nevada Risk Assessment/Management Program (Nramp), Donald H. Baepler, Anthony Hechanova

Nevada Risk Assessment/Management Program

The Nevada Risk Assessment/Management Program (NRAMP) was part of a national effort by the U.S. Department of Energy (DOE) to develop new sources of information and approaches to risk assessment, risk management, risk communication and public outreach as these objectives relate to the ecological and human health effects of radioactive and hazardous material management and site remediation activities. This final report presents a synopsis of the NRAMP effort that occurred from 1995 to 2000. Included in this report is a brief history of NRAMP including a description of the DOE Notice of Program Interest (NOPI) goals and how the NRAMP …