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Improving agent models and architectures for agent-based modelling and simulation applied to crisis management. In particular modelling of BDI agents, emotions, cognitive biases, social attachment, etc.
Designing serious games to increase awareness about climate change or natural disasters; to improve civil engagement in sustainable urban planning; to teach Artificial Intelligence to the general public; to explain social phenomena (voting procedures; sanitary policies; etc).
I discovered at the same time Agent-Based Modeling method and Companion Modelling approach during my master degrees (engeenering and artificial intelligence and decision) internship at CIRAD in 2005 and 2006 where I had the opportunity to participate as a modeller to a ComMod process (Farolfi et al., 2010).
Then, during my PhD in computer Science applied to Modeling and Simulation, I learned the Theory of Modeling and Simulation and the Discrete EVent System specification formalism and proposed a conceptual, formal and operational framework to evaluate simulation models based on the way models are used instead of their ability to reproduce the target system behavior (Bonté et al., 2012). Applied to the surveillance of Epidemics, this work was rather theoritical but very educative and structuring to formulate my further models and research questions about modeling and simulation.
From 2011 to 2013, I worked on viability theory applied to forest management at the Compex System Lab of Irstea (now Inrae) and learned about the interest of agregated models for analytical results (Bonté et al, 2012; Mathias et al, 2015).
Since 2013, I’m working for Inrae at the joint The Joint Research Unit “Water Management, Actors, Territories” (UMR G-EAU) where I’m involved in highly engaging interdisciplinary researches such as:
- The Multi-plateforme International Summer School about Agent Based Modelling and Simulation (MISSABMS)
- The development of the CORMAS (COmmon Pool Resources Multi-Agents Systems) agent-based modeling and simulation Platform (Bommel et al., 2019)
- Impacts of the adaptation to global changes using computerised serious games (Bonté et al., 2019; Bonté et al. , 2021)
- The use of experimentation to study social behaviors (Bonté et al. 2019b)
- The impact of information systems in SES trajectories (Paget et al., 2019a)
- Adaptation and transformations of traditional water management and infrastructures systems (Idda et al., 2017)
- Situational multi-agent approaches for collective irrigation (Richard et al., 2019)
- Combining psyhcological and economical experiments to study relations bewteen common pool resources situations, economical behaviours and psychological attitudes.
My research is about modelling and simulation of complex systems. My work is to use, and participate to the development of, integrative tools at the formal level (based on the Discrete EVent System Specification (DEVS) formalism), at the conceptual level (based on integrative paradigms of different forms such as Multi-Agents Systems paradigm (MAS), SES framework or viability theory), and at the level of the use of modelling and simulation for collective decision making (based on the Companion Modelling approach (ComMod)). Since 2013 and my integration in the G-EAU mixt research units, my object of studies were focused on multi-scale social and ecological systems, applied to water resource management and adaptation of territories to global change and I added experimentation to my research interest, developping methods combining agent-based model and human subjects actions.
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:
I have a backround in computer science, worked in natural resource management, and ended up with a PhD in Sustainability Sciences!
My interests are to explore aspects of sustainability, resilience, and adaptive management in social-ecological systems using agent-based models and other simulation models.
Bashar Ourabi is a principle consultant at arabianconsult of Syria where he has been chairman since 2003. He holds Bsc. Eng., A Grad. Certificate in Project engineering from the University of Central Florida; and a MS. in Public Administration from the Doha Graduate Institute in Qatar.
Bashar completed his graduate studies at Doha Institute for Graduate Studies and his undergraduate studies at the Unversity of Central Florida. His research interests lie in the area of systems modelling, ranging from theory to design to implementation. He has collaborated actively with researchers in several other disciplines of computer science, system design, and bigData Artificial Intellegence, particularly BigData Expert System and Automated decision Making.
He has served on many international posts overlooking public infrastructure design and operations, varying from public transport, urban design and operations management. These posts spanned over the the US and the Middle East including Florida, UAE and Qatar.
Bashar has served on many conferences and workshop program committees and has succesfully delivered many corporate training programs..
BigData
Artificial Intellegence
Web Based Decision Making and Expert Systems
Fuzzy Logic
AgentBased Modelling
Discret Event Simulation
Corporate Support Systems
As a data scientist, I employ a variety of ecoinformatic tools to understand and improve the sustainability of complex social-ecological systems. I also apply Science and Technology Studies lenses to my modeling processes in order to see potential ways to make social-ecological system management more just. I prefer to work collaboratively with communities on modeling: teaching mapping and modeling skills, collaboratively building data representations and models, and analyzing and synthesizing community-held data as appropriate. At the same time, I look for ways to create space for qualitative and other forms of knowledge to reside alongside quantitative analysis, using mixed and integrative methods.
Recent projects include: 1) Studying Californian forest dynamics using Bayesian statistical models and object-based image analysis (datasets included forest inventories and historical aerial photographs); 2) Indigenous mapping and community-based modeling of agro-pastoral systems in rural Zimbabwe (methods included GPS/GIS, agent-based modeling and social network analysis); 3) Supporting Tribal science and environmental management on the Klamath River in California using historical aerial image analysis of land use/land cover change and social networks analysis of water quality management processes; 4) Bayesian statistical modeling of community-collected data on human uses of Marine Protected Areas in California.
Management of Water Resources Conflicts in Halil-Rud River Basin: Application of Integrated Economic- Hydrological- Behavioral Model
Jorge is a PhD candidate of System Design Engineering at the University of Waterloo. His research activities are focused on applying agent-based models on three major areas: 1) financial markets to study the self-regulation capability of artificial markets with interacting investors and credit rating agencies; 2) the efficiency of road networks when users have access to real-time information and are able to adjust their behavior to current conditions; 3) failure probability of nuclear waste containers due to microbial- and chemical-driven corrosion.
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