Adversarial Reasoning
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Adversarial Reasoning
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Author : Alexander Kott
language : en
Publisher: CRC Press
Release Date : 2006-07-20
Adversarial Reasoning written by Alexander Kott and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-07-20 with Business & Economics categories.
The rising tide of threats, from financial cybercrime to asymmetric military conflicts, demands greater sophistication in tools and techniques of law enforcement, commercial and domestic security professionals, and terrorism prevention. Concentrating on computational solutions to determine or anticipate an adversary's intent, Adversarial Reasoning:
Adversarial Reasoning
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Author : Alexander Kott
language : en
Publisher: Chapman and Hall/CRC
Release Date : 2006-07-20
Adversarial Reasoning written by Alexander Kott and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-07-20 with Computers categories.
The rising tide of threats, from financial cybercrime to asymmetric military conflicts, demands greater sophistication in tools and techniques of law enforcement, commercial and domestic security professionals, and terrorism prevention. Concentrating on computational solutions to determine or anticipate an adversary's intent, Adversarial Reasoning: Computational Approaches to Reading the Opponent's Mind discusses the technologies for opponent strategy prediction, plan recognition, deception discovery and planning, and strategy formulation that not only applies to security issues but also to game industry and business transactions. Addressing a broad range of practical problems, including military planning and command, military and foreign intelligence, antiterrorism, network security, as well as simulation and training systems, this reference presents an overview of each problem and then explores various approaches and applications to understand the minds and negate the actions of your opponents. The techniques discussed originate from a variety of disciplines such as stochastic processes, artificial intelligence planning, cognitive modeling, robotics and agent theory, robust control, game theory, and machine learning, among others. The beginning chapters outline the key concepts related to discovering the opponent's intent and plans while the later chapters journey into mathematical methods for counterdeception. The final chapters employ a range of techniques, including reinforcement learning within a stochastic dynamic games context to devise strategies that combat opponents. By answering specific questions on how to create practical applications that require elements of adversarial reasoning while also exploring theoretical developments, Adversarial Reasoning: Computational Approaches to Reading the Opponent's Mind is beneficial for practitioners as well as researchers.
Adversarial And Uncertain Reasoning For Adaptive Cyber Defense
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Author : Sushil Jajodia
language : en
Publisher: Springer Nature
Release Date : 2019-08-30
Adversarial And Uncertain Reasoning For Adaptive Cyber Defense written by Sushil Jajodia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-30 with Computers categories.
Today’s cyber defenses are largely static allowing adversaries to pre-plan their attacks. In response to this situation, researchers have started to investigate various methods that make networked information systems less homogeneous and less predictable by engineering systems that have homogeneous functionalities but randomized manifestations. The 10 papers included in this State-of-the Art Survey present recent advances made by a large team of researchers working on the same US Department of Defense Multidisciplinary University Research Initiative (MURI) project during 2013-2019. This project has developed a new class of technologies called Adaptive Cyber Defense (ACD) by building on two active but heretofore separate research areas: Adaptation Techniques (AT) and Adversarial Reasoning (AR). AT methods introduce diversity and uncertainty into networks, applications, and hosts. AR combines machine learning, behavioral science, operations research, control theory, and game theory to address the goal of computing effective strategies in dynamic, adversarial environments.
Adversarial Reasoning
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Author : Tamir Klinger
language : en
Publisher:
Release Date : 2001
Adversarial Reasoning written by Tamir Klinger and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.
Applied Adversarial Reasoning And Risk Modeling
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Author : Noa Agmon
language : en
Publisher:
Release Date : 2011-08-07
Applied Adversarial Reasoning And Risk Modeling written by Noa Agmon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-07 with categories.
Adversarial Machine Learning
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Author : Aneesh Sreevallabh Chivukula
language : en
Publisher: Springer Nature
Release Date : 2023-03-06
Adversarial Machine Learning written by Aneesh Sreevallabh Chivukula and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-06 with Computers categories.
A critical challenge in deep learning is the vulnerability of deep learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in unintended ways. In this book, we review the latest developments in adversarial attack technologies in computer vision; natural language processing; and cybersecurity with regard to multidimensional, textual and image data, sequence data, and temporal data. In turn, we assess the robustness properties of deep learning networks to produce a taxonomy of adversarial examples that characterises the security of learning systems using game theoretical adversarial deep learning algorithms. The state-of-the-art in adversarial perturbation-based privacy protection mechanisms is also reviewed. We propose new adversary types for game theoretical objectives in non-stationary computational learning environments. Proper quantification of the hypothesis set in the decision problems of our research leads to various functional problems, oracular problems, sampling tasks, and optimization problems. We also address the defence mechanisms currently available for deep learning models deployed in real-world environments. The learning theories used in these defence mechanisms concern data representations, feature manipulations, misclassifications costs, sensitivity landscapes, distributional robustness, and complexity classes of the adversarial deep learning algorithms and their applications. In closing, we propose future research directions in adversarial deep learning applications for resilient learning system design and review formalized learning assumptions concerning the attack surfaces and robustness characteristics of artificial intelligence applications so as to deconstruct the contemporary adversarial deep learning designs. Given its scope, the book will be of interest to Adversarial Machine Learning practitioners and Adversarial Artificial Intelligence researchers whose work involves the design and application of Adversarial Deep Learning.
Collective Rationality And Collective Reasoning
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Author : Christopher McMahon
language : en
Publisher: Cambridge University Press
Release Date : 2001-08-06
Collective Rationality And Collective Reasoning written by Christopher McMahon and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-08-06 with Philosophy categories.
"This book examines the issue of rational cooperation, especially cooperation between people with conflicting moral commitments. The first part considers how the two main aspects of cooperation - the choice by a group of a particular cooperative scheme and the decision by each member to contribute to that scheme - can be understood as guided by reason. The second part explores how the activity of reasoning itself can take a cooperative form. The book is distinctive in offering an account of what people can accomplish by reasoning together, of the role of deliberation in democratic decision making, and of the negotiation of the proper use of concepts. Presenting for the first time a detailed analysis of the general problem of cooperation and collective reasoning between people with different moral commitments, this book will be of particular interest to philosophers of the social sciences and to students in political science, sociology and economics." --Cambridge Press.
Evaluating Common Sense Reasoning In Pretrained Transformer Based Language Models Using Adversarial Schemas And Consistency Metrics
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Author : Adrian Maler
language : en
Publisher:
Release Date : 2023
Evaluating Common Sense Reasoning In Pretrained Transformer Based Language Models Using Adversarial Schemas And Consistency Metrics written by Adrian Maler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
In artificial intelligence, common sense refers to simple acts of verbal reasoning. The Winograd Schema Challenge (WSC), an important test of common sense, was recently defeated by transformer-based language models. We investigate the implications of that defeat: have language models achieved common sense, or is the challenge flawed? That is, we consider the problem of reevaluating verbal reasoning in language models. We evaluate the accuracy and consistency on Winograd schemas of three important pretrained models: GPT-2, RoBERTa, and T5. We generalize the Winograd schema to a larger class of problems, called adversarial schemas, and propose an evaluation protocol for them that incorporates consistency. We create a new test of common-sense verbal reasoning made up of our adversarial schemas. Each model performs significantly worse on our test than on WSC, and no model exhibits high consistency. We find no convincing evidence of verbal reasoning by language models.
Adversarial Search And Spatial Reasoning In Real Time Strategy Games
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Author : Alberto Uriarte
language : en
Publisher:
Release Date : 2017
Adversarial Search And Spatial Reasoning In Real Time Strategy Games written by Alberto Uriarte and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Computer science categories.
For many years, Chess was the standard game to test new Artificial Intelligence (AI) algorithms for achieving robust game-playing agents capable of defeating the best human players. Nowadays, games like Go or Poker are used since they offer new challenges like larger state spaces, or non-determinism. Among these testbed games, Real-Time Strategy (RTS) games have raised as one of the most challenging. The unique properties of RTS games (simultaneous and durative actions, large state spaces, partial observability) make them a perfect scenario to test algorithms able to make decisions in dynamic and complex situations. This thesis makes a contribution towards achieving human-level AI in these complex games. Specifically, I focus on the problems of performing adversarial search in domains (1) with extremely large decision and state spaces, (2) where no forward model is available, and (3) the game state is partially observable. Additionally, I also study how spatial reasoning can be used to reduce the search space and to improve the RTS playing bots.
Adversarial Risk Analysis
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Author : David L. Banks
language : en
Publisher: CRC Press
Release Date : 2015-06-30
Adversarial Risk Analysis written by David L. Banks and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-30 with Business & Economics categories.
Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against