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He is an experienced Lecturer with a demonstrated history of working in the education management industry. He was skilled in Agent-based Modeling and Simulation, Competency Assessing and Fundamental Supply Chain Management. Strong research background and analyst with a Master’s degree focused in Logistics and Supply Chain Management from Institut Teknologi Sepuluh Nopember Surabaya and Certified Supply Chain Analyst from ISCEA International.
My research focused on pricing strategy and its impact on Supply Chain (SC) using the Agent-Based Modeling and Simulation (ABMS) approach. Currently, I’m working on an ABMS model to analyze the impact of SC Coordination on SC performance when intelligent retailers may offer price discounts based on the market’s states using Q-learning algorithm.
I am Cheick Amed Diloma Gabriel Traoré, holding a PhD in Multi-Agent System Modeling from Cheikh Anta Diop University (UCAD), Senegal. My doctoral research focused on formalizing and simulating Sahelian transhumance as a complex adaptive system. Leveraging mathematical and computational techniques, I developed agent-based models to analyze the spatio-temporal dynamics of transhumant herds, considering factors such as herd behavior, environmental conditions, and socio-economic pressures.
My background includes a Master’s and Bachelor’s in Mathematics from the University of Nazi Boni, Burkina Faso, where I developed a rectangular mesh for image processing and applied the Hough transform to detect discrete lines. My studies at the University of Nazi Boni were funded by the Burkinabe government.
For my PhD, I conducted extensive fieldwork in Senegal, collaborating with interdisciplinary teams to gather data on transhumant practices. Using this data, I developed a multi-objective optimization framework to model herd movement decisions. Furthermore, I created a real-time monitoring system for transhumant herds based on discrete mathematics. My PhD research was funded by the CaSSECS project (Carbon Sequestration and Sustainable Ecosystem Services in the Sahel).
Yiyu Wang is a PhD student in Center for Spatial Analysis and Policy (CSAP), at University of Leeds. Currently her research interests are the forward-looking simulation model of pedestrian evacuating behaviours especially in emergency situations incorporating Bayesian game theory within multi-agent systems, and their interactions with other social factors.
Sr Machine Learning Engineer, Google Developer Expert in Cloud and Machine Learning. CompTIA Security+, AWS certified Machine Learning specialty.
Generative AI, LLMs, Multi-Agent Modeling, Agent-Based Modeling, Cellular Automata, Graph Networks, Deep Learning, Social Sciences
model-based policy analysis; system dynamics; agent-based modeling
Two themes unite my research: a commitment to methodological creativity and innovation as expressed in my work with computational social sciences, and an interest in the political economy of “globalization,” particularly its implications for the ontological claims of international relations theory.
I have demonstrated how the methods of computational social sciences can model bargaining and social choice problems for which traditional game theory has found only indeterminate and multiple equilibria. My June 2008 article in International Studies Quarterly (“Coordination in Large Numbers,” vol. 52, no. 2) illustrates that, contrary to the expectation of collective action theory, large groups may enjoy informational advantages that allow players with incomplete information to solve difficult three-choice coordination games. I extend this analysis in my 2009 paper at the International Studies Association annual convention, in which I apply ideas from evolutionary game theory to model learning processes among players faced with coordination and commitment problems. Currently I am extending this research to include social network theory as a means of modeling explicitly the patterns of interaction in large-n (i.e. greater than two) player coordination and cooperation games. I argue in my paper at the 2009 American Political Science Association annual convention that computational social science—the synthesis of agent-based modeling, social network analysis and evolutionary game theory—empowers scholars to analyze a broad range of previously indeterminate bargaining problems. I also argue this synthesis gives researchers purchase on two of the central debates in international political economy scholarship. By modeling explicitly processes of preference formation, computational social science moves beyond the rational actor model and endogenizes the processes of learning that constructivists have identified as essential to understanding change in the international system. This focus on the micro foundations of international political economy in turn allows researchers to understand how social structural features emerge and constrain actor choices. Computational social science thus allows IPE to formalize and generalize our understandings of mutual constitution and systemic change, an observation that explains the paradoxical interest of constructivists like Ian Lustick and Matthew Hoffmann in the formal methods of computational social science. Currently I am writing a manuscript that develops these ideas and applies them to several challenges of globalization: developing institutions to manage common pool resources; reforming capital adequacy standards for banks; and understanding cascading failures in global networks.
While computational social science increasingly informs my research, I have also contributed to debates about the epistemological claims of computational social science. My chapter with James N. Rosenau in Complexity in World Politics (ed. by Neil E. Harrison, SUNY Press 2006) argues that agent-based modeling suffers from underdeveloped and hidden epistemological and ontological commitments. On a more light-hearted note, my article in PS: Political Science and Politics (“Clocks, Not Dartboards,” vol. 39, no. 3, July 2006) discusses problems with pseudo-random number generators and illustrates how they can surprise unsuspecting teachers and researchers.
RN [Mental Health & General], Community Mental Health Nurse (Cert.)
PG Cert. Ed
BA(Joint Hons.) Computing and Philosophy
PG(Dip.) Collaboration on Psychosocial Education [COPE]
MRES. e-Research and Technology Enhanced Learning
Nursing, Integrated, Person-Centred, Holistic (mental - physical) care.
Study and champion - “Hodges’ Health Career - Care Domains - Model” a generic conceptual framework for health and education.
‘Health career’ refers to ‘life chances’.
The care domains relate to academic subjects - knowledge and are:
SCIENCES
INTRA- INTERPERSONAL
SOCIOLOGY
POLITICAL
The blog below includes a bibliography and template link in the sidebar.
https://hodges-model.blogspot.com/
A new website remains an aspiration - using Drupal, Pharo..?
Developing ideas on Hodges’ model (not Wilfred btw) when viewed as a mathematical object, using category theory as a ‘non-mathematician’.
Work part-time still in the community in NW England.
Twitter - ‘X’ @h2cm
I am an anthropologist from the Universidad Nacional de Colombia. I am interested in ethnomusicology, art, and complex systems, especially socio-ecological. I want to understand how cultural expressions and social rules are part of a more complex system and how they are intertwined with other non-human behaviors
I am interested in modeling socio-ecological systems. I am currently working on the implementation of a seed-exchange model for understanding the role of some kinship patterns (locality and seed heritage rules) in agrobiodiversity.
I am currently enrolled as a graduate student at UC3M, working towards a MS degree in Computational and Applied Mathematics. Upon completing my current program, my intention is to further my education in Applied Economics, with a specific focus on the intersection of Climate and Development Economics.
My research pursuits center around investigating the impacts of climate change on developing nations. Additionally, I am interested in studying the repercussions of fast fashion consumption, examining its effects on working conditions, the environment, and the overall well-being of individuals in the countries where these garments are manufactured. In my ongoing master’s thesis, I employ Agent-Based Modeling to simulate the attitudes of individual consumers towards fast fashion. The model captures behavioral shifts influenced by peers, social media, and governmental factors. This research aligns with my broader interests in comprehending public perspectives on global matters, underscoring the crucial influence of individual attitudes in confronting and finding solutions to these challenges.
Development Economics, Environmental Economics, Sustainability, Environment, Climate change, Climate justice, Energy, Clean Energy, Renewable Energy, Complex systems
Dissertation: Narrative Generation for Agent-Based Models
Abstract: This dissertation proposes a four-level framework for thinking about having agent-based models (ABM) generate narrative describing their behavior, and then provides examples of models that generate narrative at each of those levels. In addition, “interesting” agents are identified in order to direct the attention of researchers to the narratives most likely to be worth spending their time reviewing. The focus is on developing techniques for generating narrative based on agent actions and behavior, on techniques for generating narrative describing aggregate model behavior, and on techniques for identifying “interesting” agents. Examples of each of these techniques are provided in two different ABMs, Zero-Intelligence Traders (Gode & Sunder, 1993, 1997) and Sugarscape (Epstein & Axtell, 1996).
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