Decisions in Risk and Reliability: An Explanatory Perspective (original) (raw)

From the Editors—Games and Decisions in Reliability and Risk

Decision Analysis, 2012

T he objective of this special issue is to introduce a new theme, the use of game and decision theory in reliability modeling and risk analysis, which was the focus of the First Symposium on Games and Decisions in Reliability and Risk (GDRR) held at the George Washington University on May 27-28, 2009. The issue considered papers presented at the Second Symposium on GDRR (http://www.mi.imati.cnr.it/conferences/gdrr11.html), held at the Hotel Villa Carlotta, Belgirate (VB), Lake Maggiore, Italy, on May 19-21, 2011, and also was open to the public for submission of papers relevant to the theme. The contributors to the special issue include Sevillano,

Adversarial issues in reliability

European Journal of Operational Research, 2018

Many reliability problems involve two or more agents with conflicting interests whose decisions affect the performance of the system at hand. Examples of such problems relevant in management practice abound and include acceptance sampling, life testing, software testing, optimal maintenance, reliability demonstration, warranties and insurance. Most earlier attempts in such problems have focused on game theoretic approaches based on Nash equilibria and related concepts. However, these require strong common knowledge assumptions which do not frequently hold in practice. We provide an alternative framework based on adversarial risk analysis to deal with such problems which avoids the strong common knowledge assumptions of game theory. We illustrate the framework through acceptance sampling and life testing problems.

Probabilistic Risk Analysis and Game Theory

Risk Analysis, 2002

The behavioral dimension matters in Probabilistic Risk Analysis (PRA) since players throughout a system incur costs to increase system reliability interpreted as a public good. Individual strategies at the subsystem level generally conflict with collective desires at the system level. Game theory, the natural tool to analyze individual-collective conflicts that affect risk, is integrated into PRA. Conflicts arise in series, parallel, and summation systems over which player(s) prefer(s) to incur the cost of risk reduction. Frequently, the series, parallel, and summation systems correspond to the four most common games in game theory, i.e., the coordination game, the battle of the sexes and the chicken game, and prisoner's dilemma, respectively.

Confidence: Its Role in Dependability Cases for Risk Assessment

37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN'07), 2007

Society is increasingly requiring quantitative assessment of risk and associated dependability cases. Informally, a dependability case comprises some reasoning, based on assumptions and evidence, that supports a dependability claim at a particular level of confidence. In this paper we argue that a quantitative assessment of claim confidence is necessary for proper assessment of risk. We discuss the way in which confidence depends upon uncertainty about the underpinnings of the dependability case (truth of assumptions, correctness of reasoning, strength of evidence), and propose that probability is the appropriate measure of uncertainty. We discuss some of the obstacles to quantitative assessment of confidence (issues of composability of subsystem claims; of the multi-dimensional, multi-attribute nature of dependability claims; of the difficult role played by dependence between different kinds of evidence, assumptions, etc). We show that, even in simple cases, the confidence in a claim arising from a dependability case can be surprisingly low.

Risk analysis and decision theory: A bridge

European Journal of Operational Research, 2018

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Highlights • Create a connection between risk analysis and decision theory • Pave the way to the use of modern decision criteria in system risk assessment • All formats of Kaplan and Garrick's risk triplets have a decision theory counterpart • Promote exchanges between two fields that benefit Decision Analysis practice

Risk's Place in Decision Rules

2001

What a delight to celebrate the achievements of Peter Gärdenfors! His monumental book, Knowledge in Flux, gives new direction to epistemology. His judicious collection of readings, compiled with Nils-Eric Sahlin, Decision, Probability, and Utility, is a standard text for many courses on decision theory. These are just two items from a long list of impressive contributions to philosophy. To highlight some of Gärdenfors's ideas, I will comment on an article from his collection on decision theory. He wrote it with his co-editor. It is entitled "Unreliable Probabilities, Risk Taking, and Decision Making." This article is a treasure of lucid and penetrating insights about rational decision making. I will review and reorganize some of those insights to show off their advantages when viewed from a new angle.

Game-theoretic computing in risk analysis

Wiley Interdisciplinary Reviews: Computational Statistics, 2012

Risk analysis, comprising risk assessment and risk management stages, is one of the most popular and challenging topics of our times because security and privacy, and availability and usability culminating at the trustworthiness of cybersystems and cyber information is at stake. The precautionary need derives from the existence of defenders versus adversaries, in an everlasting Darwinian scenario dating back to early human history of warriors fighting for their sustenance to survive. Fast forwarding to today's information warfare, whether in networks or healthcare or national security, the currently dire situation necessitates more than a hand calculator to optimize (maximize gains or minimize losses) risk due to prevailing scarce economic resources. This article reviews the previous works completed on this specialized topic of game-theoretic computing, its methods and applications toward the purpose of quantitative risk assessment and cost-optimal management in many diverse disciplines including entire range of informaticsrelated topics. Additionally, this review considers certain game-theoretic topics in depth historically, and those computationally resourceful such as Neumann's two-way zero-sum pure equilibrium and optimal mixed strategy solutions versus Nash equilibria with pure and mixed strategies. Computational examples are provided to highlight the significance of game-theoretic solutions used in risk assessment and management, particularly in reference to cybersystems and information security.