Displaying 10 of 262 results for "Dave van Wees" clear search
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.
Lu Ping is a dedicated researcher in interdisciplinary fields including artificial intelligence (AI), digital economy, technological innovation, and industrial economics. Currently serving as an Associate Research Fellow at the China Academy of Information and Communications Technology (CAICT), Lu Ping focuses on examining the impacts of digital technologies (e.g., AI, big data, and IoT) on economic growth, industrial ecosystems, policy formulation, and societal ethics through multidimensional data modeling and empirical research.
Representative Academic Contributions:
1. AI Development and Societal Implications
A Brief History of Artificial Intelligence Development in China (2017): Explored the technological evolution and policy-driven pathways of China’s AI industry.
Ethical Dilemmas Faced by AI Algorithms (2018): Analyzed ethical challenges such as algorithmic bias and data privacy, proposing governance frameworks.
A Brief History of the Evolution of Smart Hardware in China (2018): Systematically reviewed the technological iterations and market dynamics of China’s smart hardware sector.
2.Technological Innovation and Industrial Economics
An Empirical Analysis of Technological Innovation Driving Growth in Internet Companies: Evidence from A-Share Listed Internet Firms in Shanghai and Shenzhen (2019).
Research on Competitiveness Measurement of Frontier Emerging Industries Based on Data Envelopment Analysis (DEA) Models (2019).
3.Digital Economy and Market Behavior
Correlation Analysis of Crowdfunding Behavior and Funding Performance for Internet Products: A Bayesian Approach Based on JD.com Crowdfunding Data (2018): Uncovered nonlinear relationships between user participation and project success rates using crowdfunding platform data.
Analyzing the Effects of Developer and User Behavior on Mobile App Downloads (2019): Built predictive models for app market performance based on user behavior data.
4.Policy Simulation
General Equilibrium Analysis of Beijing’s Water Supply and Consumption Policies: A Computable General Equilibrium (CGE) Model-Based Approach (2015).
Impact Analysis of EU Food Safety Standards on China’s Food Industry: A Dynamic Global Trade Analysis Project (GTAP) Model-Based Study (2015).
Academic Contributions:
Pioneered interdisciplinary paradigms in industrial economics research by integrating perspectives from econometrics, data science, and sociology. Published high-impact research in AI ethics, digital economy policies, and resource-environmental economics, providing decision-making references for academia and policymakers.
My research focuses on the interdisciplinary nexus of artificial intelligence (AI), digital economy, technological innovation, and industrial economics, with an emphasis on understanding how digital technologies reshape economic structures, policy frameworks, and societal norms. Key areas of interest include:
Leigh Tesfatsion received the Ph.D. degree in economics from the University of Minnesota, Mpls., in 1975, with a minor in mathematics. She is Research Professor of Economics, Professor Emerita of Economics, and Courtesy Research Professor of Electrical & Computer Engineering, all at Iowa State University. Her principal current research areas are electric power market design and the development of Agent-based Computational Economics (ACE) platforms for the performance testing of these designs. She is the recipient of the 2020 David A. Kendrick Distinguished Service Award from the Society for Computational Economics (SCE) and an IEEE Senior Member. She has served as guest editor and associate editor for a number of journals, including the IEEE Transactions on Power Systems, the IEEE Transactions on Evolutionary Computation, the Journal of Energy Markets, the Journal of Economic Dynamics and Control, the Journal of Public Economic Theory, and Computational Economics. Online Short Bio
Agent-based computational economics (ACE); development and use of ACE test beds for the study of electric power market operations; development and use of ACE test beds for the study of water, energy, and climate change
Corinna is a lecturer in the Department of Sociology. She joined the Centre for Research in Social Simulation at the in August 2008 as a Research Fellow. Her academic background is in Philosophy (LSE, BSc MSc) and Computer Science (KCL,PhD), where her PhD Instinct for Detection developed a logic for abductive reasoning.
Currently Corinna is the PI on an AHRC Research Grant on collective reasoning in agent-based modelling, titled Collective Reasoning as a Moral Point of View. Her research interests are decision mechanisms, in particular collective decision-making, context dependency of decisions and methodological and epistemological aspects of agent-based modelling and social simulation. She has applied collective decision making to the analysis to the weakening of the Mafia in Southern Italy within the GLODERS project and published a book Modelling Norms, co-authored with Nigel Gilbert, providing a systematic analysis of the contribution of agent-based modelling to the study of social norms and deviant behaviour. Recently Corinna has been developing a teaching stream within CRESS with a periodically running short course Agent-based Modelling for the Social Scientist and the MSc Social Science and Complexity.
The goal of my research program is to improve our understanding about highly integrated natural and human processes. Within the context of Land-System Science, I seek to understand how natural and human systems interact through feedback mechanisms and affect land management choices among humans and ecosystem (e.g., carbon storage) and biophysical processes (e.g., erosion) in natural systems. One component of this program involves finding novel methods for data collection (e.g., unmanned aerial vehicles) that can be used to calibrate and validate models of natural systems at the resolution of decision makers. Another component of this program involves the design and construction of agent-based models to formalize our understanding of human decisions and their interaction with their environment in computer code. The most exciting, and remaining part, is coupling these two components together so that we may not only quantify the impact of representing their coupling, but more importantly to assess the impacts of changing climate, technology, and policy on human well-being, patterns of land use and land management, and ecological and biophysical aspects of our environment.
To achieve this overarching goal, my students and I conduct fieldwork that involves the use of state-of-the-art unmanned aerial vehicles (UAVs) in combination with ground-based light detection and ranging (LiDAR) equipment, RTK global positioning system (GPS) receivers, weather and soil sensors, and a host of different types of manual measurements. We bring these data together to make methodological advancements and benchmark novel equipment to justify its use in the calibration and validation of models of natural and human processes. By conducting fieldwork at high spatial resolutions (e.g., parcel level) we are able to couple our representation of natural system processes at the scale at which human actors make decisions and improve our understanding about how they react to changes and affect our environment.
land use; land management; agricultural systems; ecosystem function; carbon; remote sensing; field measurements; unmanned aerial vehicle; human decision-making; erosion, hydrological, and agent-based modelling
Eric Kameni holds a Ph.D. in Computer Science option modeling and application from the Radboud University of Nijmegen in the Netherlands, after a Bachelor’s Degree in Computer Science in Application Development and a Diploma in Master’s degree with Thesis in Computer Science on “modeling the diffusion of trust in social networks” at the University of Yaoundé I in Cameroon. My doctoral thesis focused on developing a model-based development approach for designing ICT-based solutions to solve environmental problems (Natural Model based Design in Context (NMDC)).
The particular focus of the research is the development of a spatial and Agent-Based Model to capture the motivations underlying the decision making of the various actors towards the investments in the quality of land and institutions, or other aspects of land use change. Inductive models (GIS and statistical based) can extrapolate existing land use patterns in time but cannot include actors decisions, learning and responses to new phenomena, e.g. new crops or soil conservation techniques. Therefore, more deductive (‘theory-driven’) approaches need to be used to complement the inductive (‘data-driven’) methods for a full grip on transition processes. Agent-Based Modeling is suitable for this work, in view of the number and types of actors (farmer, sedentary and transhumant herders, gender, ethnicity, wealth, local and supra-local) involved in land use and management. NetLogo framework could be use to facilitate modeling because it portray some desirable characteristics (agent based and spatially explicit). The model develop should provide social and anthropological insights in how farmers work and learn.
Dr. Chairi Kiourt is a research associate with the ATHENA - Research and Innovation Centre in Information, Communication and Knowledge Technologies - Xanthi’s Division, multimedia department since 2014. Also, as of December 2017, heis PostDoctoral researcher with the Hellenic Open University, School of Science and Technology, and as of 2018, visiting Lecturer at the Department of Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Greece.
In 2003, he received his BSc degree in Electrical Engineering from the Electrical Engineering Department of the Eastern Macedonia and Thrace Institute of Technology, Greece. He also received an M.Sc. in System Engineering and Management in the specialty area: A. Information and Communication Systems Management from the Democritus University of Thrace, Greece. In 2017, received his PhD in Artificial Intelligence and Software Engineering from the Hellenic Open University. He has participated in several national and European research programs and co- authored to the writing of several scientific publications in international peer-reviewed journals and conferences with judges in the fields of collective artificial intelligence, multi-agent systems, reinforcement learning agents, virtual worlds, virtual museums and gamification.
Game playing multi-agent systems, reinforcement learning, colelctive artificial intelligence, distributed computing systems, virtual worlds, gamification
Dr. William G. Kennedy, “Bill,” is continuing to learn in a third career, this time as an academic, a computational social scientist.
His first a career was in military service as a Naval Officer, starting with the Naval Academy, Naval PostGraduate School (as the first computer science student from the Naval Academy), and serving during the Cold War as part of the successful submarine-based nuclear deterrent. After six years of active duty service, he served over two decades in the Naval Reserves commanding three submarine and submarine-related reserve units and retiring after 30 years as a Navy Captain with several personal honors and awards.
His second career was in civilian public service: 10 years at the Nuclear Regulatory Commission and 15 years with the Department of Energy. At the NRC he rose to be an advisor to the Executive Director for Operations and the authority on issues concerning the reliance on human operators for reactor safety, participating in two fly-away accident response teams. He left the NRC for a promotion and to lead, as technical director, the entrepreneurial effort to explore the use of light-water and accelerator technologies for the production of nuclear weapons materials. That work led to him becoming the senior policy officer responsible for strategic planning and Departmental performance commitments, leading development of the first several DOE strategic plans and formal performance agreements between the Secretary of Energy and the President.
Upon completion of doctoral research in Artificial Intelligence outside of his DOE work, he began his third career as a scientist. That started with a fully funded, three-year post-doctoral research position in cognitive robotics at the Naval Research Laboratory sponsored by the National Academy of Science and expanding his AI background with research in experimental Cognitive Science. Upon completion, he joined the Center for Social Complexity, part of the Krasnow Institute for Advanced Study at George Mason University in 2008 where he is now the Senior Scientific Advisor. His research interests range from cognition at the individual level to models of millions of agents representing individual people. He is currently leading a multi-year project to characterize the reaction of the population of a mega-city to a nuclear WMD (weapon of mass destruction) event.
Dr. Kennedy holds a B.S. in mathematics from the U.S. Naval Academy, and Master of Science in Computer Science from the Naval PostGraduate School, and a Ph.D. in Information Technology from George Mason University and has a current security clearance. Dr. Kennedy is a member of Sigma Xi, the American Association for the Advancement of Science (AAAS), the Association for Computing Machinery (ACM), and a life member of Institute of Electrical and Electronics Engineers. He is a STEM volunteer with the Senior Scientists and Engineers/AAAS Volunteer Program for K-12 science, technology, engineering, and mathematics education in the DC-area schools.
Cognitive Science, Computational Social Science, Social Cognition, Autonomy, Cognitive Robotics
1987-1989: assistant professor at the Neuchâtel University (Switzerland)
1990-2001: full professor at the Neuchâtel University (Switzerland): artificial intelligence & software engineering
2001- : senior researcher at CIRAD in the unit “Gestion des Ressources et Environnement” (GREEN) and from 2021 “Savoirs ENvironnement Sociétés” (UMR SENS)
Former professor at the University of Neuchatel in Switzerland and now senior researcher at CIRAD in France, I am doing research on artificial intelligence since 1984. Having begun with logic programming, I naturally applied logics and its extensions (i.e. modal logics of various sorts) to specify agent behaviour. Since 1987, I moved both to embedded intelligence (using mobile robots) and multi-agent systems applied, in particular, to job-shop scheduling and complex system simulation and design. Since 2001, I exclusively work on modelling and simulation of socio-ecosystems in a multidisciplinary team on renewable resources management (GREEN). I am focusing on modelling complex systems in a multi-disciplinary (economist, agronomist, sociologists, geographers, etc.) and multi-actor (stakeholders, decision makers) setting. It includes:
- representing multiple points of view at various scales and levels on a complex socio-ecosystem, using ontologies and contexts
- representing the dynamics of such systems in a variety of formalisms (differential equations, automata, rule-based systems, cognitive models, etc.)
- mapping these representations into a simulation formalism (an extension of DEVS) for running experiments and prospective analysis.
This research is instantiated within a modelling and simulation platform called MIMOSA (http://mimosa.sourceforge.net). The current applications are the assessment of the sustainability of management transfer to local communities of the renewable ressources and the dynamics of agro-biodidversity through networked exchanges.
Klaus G. Troitzsch was a full professor of computer applications in the social sciences at the University of Koblenz-Landau since 1986 until he officially retired in 2012 (but continues his academic activities). He took his first degree as a political scientist. After eight years in active politics in Hamburg and after having taken his PhD, he returned to academia, first as a senior researcher in an election research project at the University of Koblenz-Landau, from 1986 as full professor of computer applications in the social sciences. His main interests in teaching and research are social science methodology and, especially, modelling and simulation in the social sciences.
Among his early research projects there is the MIMOSE project which developed a declarative functional simulation language and tool for micro and multilevel simulation between 1986 and 1992. Several EU funded projects were devoted to social simulation and policy modelling, the most recent from 2012 to 2015 combining data/text mining and agent-based simulation to analyse the global dynamics of extortion racket systems.
He authored, co-authored, and co-edited several books and many articles in social simulation, and he organised or co-organised a number of national and international conferences in this field. Over nearly three decades he advised and/or supervised more than 55 PhD theses, most of them in the field of social simulation. He offered annual summer and spring courses in social simulation between 1997 and 2009; more recent courses of this kind are now being organised by the European Social Simulation Assiciation and held at different places all over Europe (mostly with his contributions).
Computational social science, structuralist theory reconstruction
Displaying 10 of 262 results for "Dave van Wees" clear search