Agora : unified framework for crowd simulation research

Crowd simulation focuses on modeling the movements and behaviors of large groups of people. This area of study has become increasingly important because of its several applications in various fields such as urban planning, safety, and entertainment. In each of these domains, the presence of virtual agents exhibiting realistic behavior greatly enhances the quality of the simulations. However, the inherently multifaceted and intricate nature of human behavior presents a unique challenge, necessitating the effective combination of multiple behavior models. This thesis introduces a novel theoretical framework for modeling human behavior in crowd simulations, addressing the unresolved issue of combining a plethora of behavior models, often developed in isolation. The proposed framework decomposes human behavior into fundamental driving stimuli, which are then represented graphically through the heatmap paradigm. Subsequently, the agent behavior is influenced by the heatmaps, which guide them toward attractive areas and steer them away from repulsive locations based on the encoded stimuli. A key advantage of this approach lies in the ability to combine heatmaps using well-defined color operations, effectively integrating different aspects of human behavior. Furthermore, the heatmap paradigm facilitates objective comparison of simulation output with real-world data, employing image similarity metrics to evaluate model accuracy. To realize this framework, the thesis presents a modular software architecture designed to support various tasks involved in crowd simulation, emphasizing the separation of concerns for each task. This architecture comprises a collection of abstract modules, which are subsequently implemented using appropriate software components to realize the underlying features, resulting in the Agora framework. To assess the ability of Agora to support the various tasks involved in crowd simulation, two case studies are implemented and analyzed. The first case study simulates tourists visiting Þingvellir national park in Iceland, examining how their behavior is influenced by the visibility of the surrounding environment. The second case study employs Agora to model the thermal and density comfort levels of virtual pedestrians in an urban setting. The results demonstrate that Agora successfully supports the development, combination, and evaluation of crowd simulation models against real-world data. The authoring process, assisted by Agora, is significantly more streamlined compared to its native counterpart. The integration of multiple models is achieved by combining the heatmaps, resulting in plausible behavior, and the model assessment is made convenient through the evaluator within the framework. The thesis concludes by discussing the implications of these findings for the field of crowd simulation, highlighting the contributions and potential future directions of the Agora framework.Mannfjöldahermun fæst við gerð líkana af hreyfingu og hegðun stórra hópa af fólki. Mikilvægi þessa rannsóknasviðs hefur vaxið stöðugt vegna hagnýtingar á margvíslegum vetvangi, eins og til dæmis á vetvangi borgarskipulags, öryggis og afþreyingar. Þegar sýndarmenni hegða sér á sannfærandi hátt, leiðir það til betri hermunar fyrir þessi notkunarsvið. En mannleg hegðun er í eðli sínu margbrotin og flókin og því er það sérstök áskorun við smíði sýndarmenna að sameina, með áhrifaríkum hætti, mörg mismunandi hegðunarlíkön. Þessi ritgerð kynnir nýja fræðilega umgjörð líkanasmíði mannlegrar hegðunar fyrir mannfjöldahermun, sem tekur á þeim óleysta vanda að sameina fjölda hegðunarlíkana, sem oft eru þróuð með aðskildum hætti. Umgjörðin brýtur mannlega hegðun niður í grundvallar drifáreiti, sem eru sett fram grafískt útfrá hugmyndafræði hitakorta. Sýndarmennin hegða sér síðan undir áhrifum frá hitakortunum, sem vísa þeim í áttina að aðlaðandi svæðum og stýra þeim burt frá fráhrindandi svæðum, útfrá hinu umritaða áreiti. Lykilkostur þessarar nálgunar er sá eiginleiki að geta blandað saman hitakortum með vel skilgreindum litaaðgerðum, sem eru þá í raun samþætting mismunandi hliða mannlegrar hegðunar. Hitakortshugmyndafræðin auðveldar ennfremur hlutlægan samanburð hermunarúttaks og raungagna með notkun myndsamanburðarmælinga, til að meta nákvæmni líkana. Varðandi útfærslu, þá kynnir þessi ritgerð einingadrifna hugbúnaðarhögun sem er hönnuð til að styðja við ýmsa ferla mannfjöldahermunar, með áherslu á aðskilnað helstu viðfangsefna hvers ferlis. Þessi högun inniheldur safn huglægra eininga, sem síðan eru útfærðar með viðeigandi hugbúnaðarhlutum, sem raungera undirliggjandi eiginleika. Útkoman er sjálf Agora umbjörðin. Tvö sýnidæmi eru útfærð og greind til að meta getu Agoru til að styðja við ýmis mannfjöldahermunarverkefni. Fyrra dæmið hermir eftir ferðamönnum sem heimsækja Þingvallaþjóðgarð, og skoðar hvernig hegðun þeirra verður fyrir áhrifum sýnileika umhverfisins sem umleikur þá. Seinna dæmið nýtir Agoru til að smíða líkan af hitauppstreymis- og þéttleikaþægindum hjá sýndarvegfarendum í borgarumhverfi. Niðurstöðurnar sýna góðan árangur Agoru við að styðja þróun, samþættingu og mat mannfjöldahermunarlíkana gagnvart raungögnum. Þróunarferlið er verulega þjálla með Agoru en með hefðbundnum aðferðum. Samþætting margra líkana tókst með blöndun hitakorta, möguleg hegðun var framkölluð og mat á líkönunum varð þægilegra með umgjörðinni. Ritgerðinni lýkur með því að fjalla um áhrif þessara niðurstaðna á svið mannfjöldahegðunar, með áherslu á nýstálegt framlag þessarar rannsóknar og mögulega framtíðarþróun Agora umgjarðarinnar

Symbolic verification of event–condition–action rules in intelligent environments

In this paper we show how state-of-the art SMT-based techniques for software verification can be employed in the verification of event–condition–action rules in intelligent environments. Moreover, we exploit the specific features of intelligent environments to optimise the verification process. We compare our approach with previous work in a detailed evaluation section, showing how it improves both performance and expressivity of the language for event–condition–action rules

Automatic abstraction and refinement for simulations with adaptive level of detail

Optimizing the level of detail of a simulation involves avoiding the computation of unnecessary features, if doing so is transparent to one or more observers. This concept dates back to graphic level of detail which has already been thoroughly studied, and there are various techniques that adjust the rendering quality. Non trivial simulations, in addition to the graphic component, also have a model that is responsible for the behavior of intelligent agents in the environment. Modern computing allows simulations to be always larger and more complex, thus requiring an ever growing amount of resources to function. In this dissertation we propose a system that is able to decompose a simulation in different layers of abstraction, adjust the level of detail of the simulation according to the observer's perception of the world, and present the resulting visual representation to the user. In particular, my contribution to the system revolves around devising ways of understanding when to switch between different levels of detail, and how to perform the adjustment without altering the consistency of the simulation with regards to the user's perception of the environment

Automatic Abstraction and Refinement for Simulations with Adaptive Level of Detail

Optimizing the level of detail of an interactive simulation involves maximizing its perceived scope while minimizing the computational resources that are required to maintain it. Using varying levels of detail is common in computer graphics, but the challenges of doing so in simulations remain substantially less explored. The interactive simulations of video games often govern the behaviour of intelligent agents in the environment, and such behaviours can take substantial computational resources to maintain. As the ambitions of designers and players demand larger and more complex simulations, new strategies are needed to disassociate the perceived scope of a simulation with its computational needs. To this end, we propose a way to automatically adjust between different levels of detail in an interactive, narrative planning context, while simultaneously identifying and visualizing the elements that can currently be perceived

Italian pediatric nutrition survey

Introduction the prevalence of malnutrition in children and its impact on clinical outcomes is underrecognized by clinicians in Italy as well as worldwide. A novel definition of pediatric malnutrition has been recently proposed by a working group of the Academy of Nutrition and Dietetics and American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.), based on the correlation between illness and the use of zscores of anthropometric measurements. Aim to investigate the prevalence of malnutrition and related nutritional support among hospitalized children in Italy, in a nationwide survey performed in a single day (16/4/2015). Methods an open access website (http://nday.biomedia.net) was used to collected data from 73 hospitals and 101 wards in 14 Italian regions (1994 patients). Anonymous information was collected on hospitals' characteristics, patient's anthropometry, admission diagnosis, presence of chronic diseases and use of nutritional support: oral nutritional supplements (ONS), enteral nutrition (EN) or parenteral nutrition (PN). Z-scores of anthropometric measurements, calculated with Epi Info 7.1.5, defined nutritional status: wasting was identified by BMI or Weight-for-Length z-score (<â\u88\u921 mild, <â\u88\u922 moderate, <â\u88\u923 severe), stunting by Height-for-Age Z-score <â\u88\u922. WHO 2006 and CDC 2000 growth charts were used respectively for children younger and older than 2 years old. Results 1790 complete records were obtained for hospitalized patients aged 0â\u80\u9320 years, with median age 6.16 (0.1â\u80\u9320 years and 53.3% males). 52.9% were aged 0â\u80\u936 years and 58.8% of children suffered from chronic diseases. Wasting was detected in 28.7% of the total sample with higher occurrence observed in age ranges 0â\u80\u936 and 14â\u80\u9320 years, while 17.3% of patients showed stunting; surprisingly almost 27% of them were aged 0â\u80\u932. A ranking of the admission diagnosis with the highest rate of malnutrition was complied. The prevalence of wasting was significantly (p < 0.005) higher amongst children with chronic diseases (34.1% vs. 27.1%); stunting prevalence tripled in patients with chronic disease (24.5% vs. 8.3%). Only 23.5% of malnourished children (17%, 25.6% and 36.7%, respectively mild, moderate and severe malnutrition) received nutritional support: 11.7% received oral nutrition supplements (ONS, modular or complete), 11.5% enteral nutrition (EN, 6.4% via nasogastric tube, 5.1% via gastrostomy) and 6.8 % received parenteral nutrition (PN); in some patients a combination of two. Nutritional support is more commonly used among stunting patients, 39.5% of children under treatment. Conclusion Malnutrition of any grade was observed in nearly 1/3 and stunting in 17% of the reported hospitalized children, and it is likely to be underrecognized as the nutritional support reached only a small part of the malnourished children