Displaying 10 of 499 results for "Aad Kessler" clear search
I am a spatial (GIS) agent-based modeler i.e. modeler that simulates the impact of various individual decisions on the environment. My work is mainly methodological i.e. I develop tools that make agent-based modeling (ABM) easier to do. I especially focus on developing tools that allow for evaluating various uncertainties in ABM. One of these uncertainties are the ways of quantifying agent decisions (i.e. the algorithmic representation of agent decision rules) for example to address the question of “How do the agents decide whether to grow crops or rather put land to fallow?”. One of the methods I developed focuses on representing residential developers’ risk perception for example to answer the question: “to what extent is the developer risk-taking and would be willing to build new houses targeted at high-income families (small market but big return on investment)?”. Other ABM uncertainties that I evaluate are various spatial inputs (e.g. different representations of soil erosion, different maps of environmental benefits from land conservation) and various demographics (i.e. are retired farmers more willing to put land to conservation?). The tools I develop are mostly used in (spatial) sensitivity analysis of ABM (quantitative, qualitative, and visual).
I have been working in the software implementation of different kinds of complex networks inspired in real-life populations. My software may be classified on several categories: complex networks, Aedes aegypti development, dengue epidemics, cultural behavior of populations. I am also researching in education of Deaf people in Colombia.
My name is Elise but everybody calles me JobDiva! I’m a highly-skilled career writer with over 15 years of experience in resume writing and creating a story-telling cover letter. My approach in creating compelling cv for each job seeker demonstrated 100% success as an invitation for an interview. My aim is every talented person to find their calling. My goal is to help an experienced professional (or someone who is still taking their first steps in their career) to get what they want and achieve success in their career. This is an example of agriculture cover letter examples that will help you move forward in life. I hope the information I have provided will be useful to you! It doesn’t matter that you have no experience, the main thing is how hard you are willing to work!
This is Saeed Abdolhosseini. I am very interested in the area of agent based modeling and it is about 3 years that I am working on Agent-Based Modeling. I have a good experience of working with Netlogo &Repast simphony & Anylogic. I have developed a few ABM application.
Specialties: Agent-based models of social systems
Agent Based Modeling
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
Dr. Gravel-Miguel currently works as a Postdoctoral Research Scholar for the Institute of Human Origins at Arizona State University. She does research in Archaeology and focuses on the Upper Paleolithic of Southwest Europe. She currently works on projects ranging from cultural transmission to human-environment interactions in prehistory.
Archaeology, GIS, ABM, social networks, portable art, ornaments, data science
I develop simulation tools for generating what-if scenarios for decision making. I predominantly use Agent-Based Modelling (ABM) technique as most of my simulations model complex systems. In some cases, I have extended existing tools with modifications to model the given system. Although the tools are meant for research purposes, I have followed industry friendly delivery mechanisms, such as unit-tests, automated builds and delivery on cloud platforms.
Research Assistant Professor at the Virginia Modeling, Analysis and Simulation Center at Old Dominion University. I work in the Storymodelers research group at VMASC where we use computational modeling approaches to try to understand complex social issues. Our main project is currently focused on modeling the dynamics of how host communities respond to the rapid influx of forced migrants.
Community assembly after intervention by coral transplantation
The potential of transplantation of scleractinian corals in restoring degraded reefs has been widely recognized. Levels of success of coral transplantation have been highly variable due to variable environmental conditions and interactions with other reef organisms. The community structure of the area being restored is an emergent outcome of the interaction of its components as well as of processes at the local level. Understanding the
coral reef as a complex adaptive system is essential in understanding how patterns emerge from processes at local scales. Data from a coral transplantation experiment will be used to develop an individual-based model of coral community development. The objectives of the model are to develop an understanding of assembly rules, predict trajectories and discover unknown properties in the development of coral reef communities in the context of reef restoration. Simulation experiments will be conducted to derive insights on community trajectories under different disturbance regimes as well as initial transplantation configurations. The model may also serve as a decision-support tool for reef restoration.
In this paper, we explore the dynamic of stock prices over time by developing an agent-based market. The developed artificial market comprises of heterogeneous agents occupied with various behaviors and trading strategies. To be specific, the agents in the market may expose to overconfidence, conservatism or loss aversion biases. Additionally, they may employ fundamental, technical, adaptive (neural network) strategies or simply being arbitrary agents (zero intelligence agents). The market has property of direct interaction. The environment takes the form of network structure, namely, it takes the manifestation of scale-free network. The information will flow between the agents through the linkages that connect them. Furthermore, the tax imposed by the regulator is investigated. The model is subjected to goodness of fit to the empirical observations of the S\&P500. The fitting of the model is refined by calibrating the model parameters through heuristic approach, particularly, scatter search. Conclusively, the parameters are validated against normality, absence of correlations, volatility cluster and leverage effect using statistical tests.
Displaying 10 of 499 results for "Aad Kessler" clear search