<?xml version="1.0" encoding="UTF-8"?><xml><records><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%">Lakshika, E.</style></author><author><style face="normal" font="default" size="100%">Barlow, M.</style></author><author><style face="normal" font="default" size="100%">Easton, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fidelity and complexity of standing group conversation simulations: A framework for the evolution of Multi Agent Systems through bootstrapping human aesthetic judgments</style></title><secondary-title><style face="normal" font="default" size="100%">Evolutionary Computation (CEC), 2012 IEEE Congress on</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10-15 June 2012</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Brisbane, QLD</style></pub-location><isbn><style face="normal" font="default" size="100%">978-1-4673-1508-1</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;article&quot; style=&quot;color: rgb(51, 51, 51); font-family: Arial, sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: 24.012800216674805px; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px;&quot;&gt;&lt;p&gt;Simple rule based Multi Agent Systems are widely used in the fields of social simulations and game artificial intelligence in order to incorporate the complexity and richness of action and interaction into the characters in the virtual environments while keeping computational cost low. This paper presents an approach to synthesize the spatio-temporal dynamics of groups in standing conversation: four simple spatial rules form the building-blocks and a framework to automatically evolve rule and the parameter space by bootstrapping a-priori human judgment on the aesthetic quality of the simulations is introduced. The framework consists of a Genetic Algorithm and a scorer (fitness function) developed based on a machine learning system trained using human evaluations. The results of the study suggest that the framework is capable of deriving optimal rule and parameter combinations utilizing only a relatively small set of human scored training data. Further, the relationship between rule-complexity and visual fidelity is explored.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;article-ftr&quot; style=&quot;padding-top: 4px; color: rgb(51, 51, 51); font-family: Arial, sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: 24.012800216674805px; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px;&quot;&gt;&amp;nbsp;&lt;/div&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lakshika, E.</style></author><author><style face="normal" font="default" size="100%">Barlow, M.</style></author><author><style face="normal" font="default" size="100%">Easton, A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Co-evolving semi-competitive interactions of sheepdog herding behaviors utilizing a simple rule-based multi agent framework</style></title><secondary-title><style face="normal" font="default" size="100%">Artificial Life (ALIFE), 2013 IEEE Symposium on</style></secondary-title></titles><dates><pub-dates><date><style  face="normal" font="default" size="100%">April 2013</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Singapore</style></pub-location><isbn><style face="normal" font="default" size="100%">2160-6374</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;article&quot; style=&quot;color: rgb(51, 51, 51); font-family: Arial, sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: 24.012800216674805px; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px;&quot;&gt;&lt;p&gt;Sheepdog herding behaviors demonstrate an interesting form of interactions between two classes of agents - sheep and the dog. The nature of the interactions between sheep and the dog takes a special form of competition which is different to the traditional prey-predator interactions where the success of prey depends on the failure of the predator and vice versa. In consequent, the development of an appropriate objective function to efficiently co-evolve successful sheepdog herding behaviors becomes challenging. This paper presents a framework to efficiently co-evolve sheepdog herding behaviors utilizing the simple rule based agent approach in order to derive high fidelity behavior dynamics and discusses the challenges involved in the process.&lt;/p&gt;&lt;/div&gt;&lt;div class=&quot;article-ftr&quot; style=&quot;padding-top: 4px; color: rgb(51, 51, 51); font-family: Arial, sans-serif; font-size: 15px; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: 24.012800216674805px; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px;&quot;&gt;&amp;nbsp;&lt;/div&gt;</style></abstract></record></records></xml>