Community

Displaying 10 of 49 results for "Jonathan Levine" clear search

Steven Doubleday Member since: Sun, Jun 30, 2013 at 06:43 PM

BS, Sociology/Anthropology, Haverford College

Graduate studies in mathematical behavioral sciences, with focus on developing cognitively plausible agent models for simulation of economic problems.

Ismael Chaile Member since: Wed, Dec 11, 2013 at 06:29 PM Full Member

Ph.D. with research line in Multi-agent systems and Distributed systems (robots, IoT), Master In Science in Micro and Nanoelectronic, Master in General Direcction and Strategic Planning, Electronic Engineer

I have been researching in synchronization between agent-based-models (ABM) and multi robot systems used in logistic and manufacturing. I use Netlogo as ABM.
I develop and agile methodology to use the same ABM as supervisory control and data aquisition (SCADA). The framework works fine and I test it in two SCADAs, which you can see in my youtube channel (http://www.youtube.com/channel/UCJIb_UL-ak98F5OZxOHL0FQ).

kwall-affiliate Member since: Wed, Jan 22, 2014 at 05:15 AM

Xiaotian Wang Member since: Fri, Mar 28, 2014 at 02:23 AM

PHD of Engineering in Modeling and Simulation, Proficiency in Agent-based Modeling

Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.

Jonathan Paige Member since: Mon, Apr 21, 2014 at 09:28 PM Full Member

Jonathan Ozik Member since: Sat, Oct 04, 2014 at 04:57 PM

Elvin Elvin Member since: Tue, Oct 07, 2014 at 04:02 AM

Mora Lening Member since: Wed, Nov 05, 2014 at 04:01 PM Full Member

Giorgio Gosti Member since: Tue, Jan 13, 2015 at 12:50 PM

Magistral Degree, Physics, University of Rome, “La Sapienza”, Italy, Dottorato, Computer Science and Mathemaatics, University of Perugia, Italy, PhD, Institute for Mathematical Behavioral Sciences, Social Science, University of California, Irvine

My research focuses pn the intersection between game theory, social networks, and multi-agent simulations. The objectives of this scientific endeavor are to inform policy makers, generate new technological applications, and bring new insight into human and non-human social behavior. My research focus is on the transformation of cultural conventions, such as signaling and lexical forms, and on many cell models models of stem cell derived clonal colony.

Because the models I analyze are formally defined using game theory and network theory, I am able to approach them with different methods that range from stochastic process analysis to multi-agent simulations.

Andreas Angourakis Member since: Wed, Feb 03, 2016 at 04:01 PM

PhD in Archaeology (University of Barcelona), Master Degree in Prehistorical Archaeology (Autonomous University of Barcelona), Degree in Sociology (Autonomous University of Barcelona), Degree in Humanities (Autonomous University of Barcelona)

I am a computational archaeologist with a strong background in humanities and social sciences, specialising in simulating socioecological systems from the past.

My main concern has been to tackle meaningful theoretical questions about human behaviour and social institutions and their role in the biosphere, as documented by history and archaeology. My research focuses specifically on how social behaviour reflects long-term historical processes, especially those concerning food systems in past small-scale societies. Among the aspects investigated are competition for land use between sedentary farmers and mobile herders (Angourakis et al. 2014; 2017), cooperation for food storage (Angourakis et al. 2015), origins of agriculture and domestication of plants (Angourakis et al. 2022), the sustainability of subsistence strategies and resilience to climate change (Angourakis et al. 2020, 2022). He has also been actively involved in advancing data science applications in archaeology, such as multivariate statistics on archaeometric data (Angourakis et al. 2018) and the use of computer vision and machine learning to photographs of human remains (Graham et al. 2020).

As a side, but not less important interest, I had the opportunity to learn about video game development and engage with professionals in Creative Industries. In one collaborative initiative, I was able to combine my know-how in both video games and simulation models (\href{https://doi.org/10.1007/978-3-030-92843-8_15}{Szczepanska et al. 2022}).

  • Modeling human-plant interactions in the origin of agriculture: Multiparadigmatic modeling and simulation (ABM, System Dynamics) of the interaction between humans and plants during domestication.
  • Modeling cooperation in small-scale food economies: Agent-based modeling and simulation of the mechanisms involved in the emergence and disruption of cooperative behavior and institutions.
  • Models of resource metabolism: study of matter, information and energy flows in systems with living agents at all scales.
  • Modeling prehistoric hunting: modeling hunting at the scale of individuals to understand the immediate constraints of hunting as an ecological, economical and social activity.
  • Modeling the interaction between herding and farming in arid environments: Agent-based modeling and simulation of the mechanisms involved in the formation and change of agro-pastoral land use patterns (sedentary farming and mobile herding) in the arid Afro-Eurasia.
  • Models for games, games for models: Explore the intersection between modeling in Archaeology and game design, aiming to improve our understanding of the long-term implications of human behavior.

Displaying 10 of 49 results for "Jonathan Levine" clear search

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept