<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hussein A. Abbass</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Art of Red Teaming</style></title><secondary-title><style face="normal" font="default" size="100%">Computational Red Teaming</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham </style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lam T. Bui</style></author><author><style face="normal" font="default" size="100%">Axel Bender</style></author><author><style face="normal" font="default" size="100%">Michael Barlow</style></author><author><style face="normal" font="default" size="100%">Hussein A. Abbass</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multiagent-Based Approach for Risk Analysis in Mission Capability Planning</style></title><secondary-title><style face="normal" font="default" size="100%">Agent-Based Evolutionary Search</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><number><style face="normal" font="default" size="100%">5</style></number><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin </style></pub-location><volume><style face="normal" font="default" size="100%">pp  77-96</style></volume><isbn><style face="normal" font="default" size="100%">978-3-642-13425-8</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;col-main has-full-enumeration&quot; id=&quot;kb-nav--main&quot; style=&quot;border: 0px; font-family: 'Helvetica Neue', Arial, Helvetica, sans-serif; font-size: 13px; font-style: normal; font-variant: normal; font-weight: normal; line-height: 13px; margin: 0px 0px 0px 40px; padding: 0px; vertical-align: baseline; outline: 0px; display: inline; width: 580px; float: left; position: relative; color: rgb(51, 51, 51); letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255);&quot;&gt;&lt;div class=&quot;abstract-content formatted&quot; style=&quot;border: 0px; font-family: inherit; font-size: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline; outline: 0px; display: block;&quot;&gt;&lt;p&gt;In this chapter, we propose a multiagent-based approach for risk analysis in military capability planning. A hierarchical system is introduced that has two layers: an Option Production Layer (OPL) to find all possible options for the given planning problem, and a Risk Tolerance Layer (RTL) in which DMs&amp;rsquo; acceptance of risk is evolved. The OPL uses metaheuristic techniques such as evolutionary algorithms to deal with multi-objectivity of a class of NP-hard resource investment problems, called the Mission Capability Planning Problem (MCPP), under the presence of risk factors. This problem has at least two inherent conflicting objectives: minimizing the cost of investment in resources as well as optimizing the makespan of plans. The framework allows for the addition of a risk-based objective to the problem in order to support risk assessment during the planning process. The RTL is run by a multi-agent system which simulates the risk attitudes of DM. The system determines different types of attitudes towards risk with each type applying to a sub-set of MCPP solutions. The goal of each agent is to maximize its risk tolerance levels with respect to a given subset of solutions determined in the OPL. Risk tolerance levels are used as surrogates for risk attitudes. The hierarchical system is flexible in terms of using a feedback mechanism when necessary. The RTL uses information from the OPL and can itself return some hyper-information to guide the OPL further. In a case study, we use a mission planning scenario to validate our proposal. The results from this study demonstrate the advantage of our proposed system. A diverse set of agents was found; hence different types of options can be grouped and offered to the decision-makers.&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;col-aside&quot; id=&quot;kb-nav--aside&quot; style=&quot;border: 0px; font-family: 'Helvetica Neue', Arial, Helvetica, sans-serif; font-size: 13px; font-style: normal; font-variant: normal; font-weight: normal; line-height: 13px; margin: 0px 0px 0px 40px; padding: 0px; vertical-align: baseline; outline: 0px; display: inline; width: 240px; float: left; color: rgb(51, 51, 51); letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255);&quot;&gt;&lt;div class=&quot;cover&quot; style=&quot;border: 0px; font-family: inherit; font-size: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline; outline: 0px; display: block;&quot;&gt;&lt;div class=&quot;look-inside cover-image-animate&quot; style=&quot;border: 0px; font-family: inherit; font-size: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline; outline: 0px; display: block; min-height: 188px; position: relative; max-width: 170px; text-decoration: none;&quot;&gt;&amp;nbsp;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</style></abstract><section><style face="normal" font="default" size="100%">Adaptation, Learning, and Optimization</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ang Yang</style></author><author><style face="normal" font="default" size="100%">Hussein A. Abbass</style></author><author><style face="normal" font="default" size="100%">Ruhul Sarker</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Land Combat Scenario Planning: A Multiobjective Approach</style></title><secondary-title><style face="normal" font="default" size="100%">Simulated Evolution and Learning</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><number><style face="normal" font="default" size="100%">4247</style></number><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><isbn><style face="normal" font="default" size="100%">978-3-540-47332-9</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;col-main has-full-enumeration&quot; id=&quot;kb-nav--main&quot; style=&quot;border: 0px; font-family: 'Helvetica Neue', Arial, Helvetica, sans-serif; font-size: 13px; font-style: normal; font-variant: normal; font-weight: normal; line-height: 13px; margin: 0px 0px 0px 40px; padding: 0px; vertical-align: baseline; outline: 0px; display: inline; width: 580px; float: left; position: relative; color: rgb(51, 51, 51); letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255);&quot;&gt;&lt;div class=&quot;abstract-content formatted&quot; style=&quot;border: 0px; font-family: inherit; font-size: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline; outline: 0px; display: block;&quot;&gt;&lt;p&gt;The simulation of land combat operations is a complex task. The space of possibilities is exponential and the performance criteria are usually in conflict; thus finding a sweet spot in this complex search space is a hard task. This paper focuses on the effect of population size and mutation rate on the performance of NSGA&amp;ndash;II, as the evolutionary multiobjective optimization technique, to decide on the composition of forces using a complex land combat multi-agent scenario planning tool.&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;col-aside&quot; id=&quot;kb-nav--aside&quot; style=&quot;border: 0px; font-family: 'Helvetica Neue', Arial, Helvetica, sans-serif; font-size: 13px; font-style: normal; font-variant: normal; font-weight: normal; line-height: 13px; margin: 0px 0px 0px 40px; padding: 0px; vertical-align: baseline; outline: 0px; display: inline; width: 240px; float: left; color: rgb(51, 51, 51); letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255);&quot;&gt;&lt;div class=&quot;cover&quot; style=&quot;border: 0px; font-family: inherit; font-size: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline; outline: 0px; display: block;&quot;&gt;&lt;div class=&quot;look-inside cover-image-animate&quot; style=&quot;border: 0px; font-family: inherit; font-size: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline; outline: 0px; display: block; min-height: 188px; position: relative; max-width: 170px; text-decoration: none;&quot;&gt;&amp;nbsp;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</style></abstract><reprint-edition><style face="normal" font="default" size="100%">6th International Conference, SEAL 2006, Hefei, China, October 15-18, 2006. </style></reprint-edition></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ang Yang</style></author><author><style face="normal" font="default" size="100%">Hussein A. Abbass</style></author><author><style face="normal" font="default" size="100%">Ruhul Sarker</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Risk assessment of capability requirements using WISDOM-II</style></title><secondary-title><style face="normal" font="default" size="100%">Complex System</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">January 16, 200</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">60390A </style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p style=&quot;text-align:start&quot;&gt;The analysis of capability requirements is very important for military operational decision. It assists defence analysts to make decisions at all strategic, operational and tactical levels. However it tends to be extremely expensive and time-consuming because of the complexity under the military command, control and communication environment. Information technologies, such as red teaming, complex adaptive systems and agent based systems, can facilitate such analysis in a well-structured and systematic way through computer simulations. Based on these technologies, a promising agent-based combat simulation system - WISDOM-II is built. In this paper, we conduct a series of analysis to evaluate the effect of different capability configurations on the performance of different force compositions.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ang Yang</style></author><author><style face="normal" font="default" size="100%">Hussein A. Abbass</style></author><author><style face="normal" font="default" size="100%">Ruhul Sarker</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evolving agents for network centric warfar</style></title><secondary-title><style face="normal" font="default" size="100%">GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06-2005</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">ACM </style></publisher><pub-location><style face="normal" font="default" size="100%">New York, NY, USA ©2005</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span style=&quot;background-color:rgb(255, 255, 255); color:rgb(0, 0, 0); font-family:verdana,arial,helvetica,sans-serif&quot;&gt;The advances in information technology largely influence our life style in various aspects. The changes in the underlying economics, information technology, business processes and organizations are affecting the very character of war and are leading to the fundamental shift from platform-centric warfare to network centric warfare (NCW), also known as network centric operation (NCO) [1]. Since its emergence in 1983 [10], the debate between proponents and opponents is hotly continuous. The proponents suggest that networked entities may produce information superiority, which in turn dramatically increases combat power. The theory that power is increasingly derived from information sharing, knowledge sharing and command speeding up has been supported by results of recent military operational experience [4]. The advantages of NCW have been recognized as:Small-size networked forces can perform missions effectively at a lower cost&lt;/span&gt;&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ang Yang</style></author><author><style face="normal" font="default" size="100%">Hussein A. Abbass</style></author><author><style face="normal" font="default" size="100%">Ruhul Sarker</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">WISDOM-II: A Network Centric Model for Warfare</style></title><secondary-title><style face="normal" font="default" size="100%">Knowledge-Based Intelligent Information and Engineering Systems</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><number><style face="normal" font="default" size="100%">3683</style></number><publisher><style face="normal" font="default" size="100%">Springer Berlin Heidelberg</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin </style></pub-location><pages><style face="normal" font="default" size="100%">9th International Conference, KES 2005, Melbourne, Australia, September 14-16, 2005, Proceedings, Part III</style></pages><isbn><style face="normal" font="default" size="100%">978-3-540-31990-0</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;col-main has-full-enumeration&quot; id=&quot;kb-nav--main&quot; style=&quot;border: 0px; font-family: 'Helvetica Neue', Arial, Helvetica, sans-serif; font-size: 13px; font-style: normal; font-variant: normal; font-weight: normal; line-height: 13px; margin: 0px 0px 0px 40px; padding: 0px; vertical-align: baseline; outline: 0px; display: inline; width: 580px; float: left; position: relative; color: rgb(51, 51, 51); letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255);&quot;&gt;&lt;div class=&quot;abstract-content formatted&quot; style=&quot;border: 0px; font-family: inherit; font-size: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline; outline: 0px; display: block;&quot;&gt;&lt;p&gt;With recognition of warfare as a complex adaptive system, a number of agent based distillation systems for warfare have been developed and adopted to study the dynamics of warfare and gain insight into military operations. These systems have facilitated the analysis and understanding of combat. However these systems are unable to meet the new needs of defence arising from the deeper understanding of warfare and the emergence of the theory of network centric warfare. In this paper, we propose a network centric model which provides a new approach to understand and analyse the dynamics of both platform centric and network centric warfare.&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class=&quot;col-aside&quot; id=&quot;kb-nav--aside&quot; style=&quot;border: 0px; font-family: 'Helvetica Neue', Arial, Helvetica, sans-serif; font-size: 13px; font-style: normal; font-variant: normal; font-weight: normal; line-height: 13px; margin: 0px 0px 0px 40px; padding: 0px; vertical-align: baseline; outline: 0px; display: inline; width: 240px; float: left; color: rgb(51, 51, 51); letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: rgb(255, 255, 255);&quot;&gt;&lt;div class=&quot;cover&quot; style=&quot;border: 0px; font-family: inherit; font-size: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline; outline: 0px; display: block;&quot;&gt;&lt;div class=&quot;look-inside cover-image-animate&quot; style=&quot;border: 0px; font-family: inherit; font-size: inherit; font-style: inherit; font-variant: inherit; font-weight: inherit; line-height: inherit; margin: 0px; padding: 0px; vertical-align: baseline; outline: 0px; display: block; min-height: 188px; position: relative; max-width: 170px; text-decoration: none;&quot;&gt;&amp;nbsp;&lt;/div&gt;&lt;/div&gt;&lt;/div&gt;</style></abstract></record></records></xml>