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Bruno Bonté Member since: Mon, Feb 13, 2017 at 09:44 AM Full Member

PhD in Computer Science applied to Modelling and Simulation, University of Montpellier 2, Master degree in Computer Science applied to Artificial Intelligence and Decision in Paris 6 University of Pierre and Marie Curry

Master Degree

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).

PhD

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.

Post-Doc

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).

G-EAU

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.

Ping Lu Member since: Fri, Feb 24, 2017 at 04:47 AM Full Member Reviewer

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:

  1. Artificial Intelligence & Digital Transformation
    Ethical and Governance Challenges of AI: Investigating algorithmic bias, data privacy, and accountability in AI systems; proposing frameworks for ethical AI development and deployment.
    AI Adoption and Economic Impact: Analyzing how AI-driven automation and innovation influence productivity, labor markets, and industrial competitiveness.
  2. Digital Economy & Platform Markets
    Crowdfunding, Sharing Economy, and Digital Platforms: Examining user behavior, market dynamics, and performance drivers in emerging digital ecosystems (e.g., crowdfunding campaigns, app markets).
    Digital Innovation and Entrepreneurship: Studying the role of technological innovation in firm growth, particularly in internet-based industries.
  3. Technological Innovation & Industrial Policy
    Innovation-Driven Industrial Competitiveness: Developing quantitative models (e.g., DEA, CGE) to assess the efficiency and competitiveness of emerging industries under technological disruption.
    Policy Evaluation and Simulation: Using computational modeling to analyze the economic and industrial impacts of trade policies, environmental regulations, and technological standards.
  4. Resource Economics & Sustainable Development
    Water Resource Management and Policy: Evaluating the economic and environmental trade-offs of water conservation policies through general equilibrium modeling.
    Global Trade and Food Security: Assessing the impacts of international trade regulations (e.g., food safety standards) on domestic industries and global supply chains.
  5. Cross-Disciplinary Methodological Innovation
    Integrating econometrics, data science, and behavioral economics to enhance the rigor and relevance of industrial and policy research.
    Leveraging big data analytics, machine learning, and agent-based modeling to uncover complex relationships in digital markets and technological ecosystems.

Simon Johanning Member since: Mon, Jul 17, 2017 at 09:51 AM

BMus Composition & Music Technology, MA DDC: Music Technology

IRPact - An integrated agent based modeling approach in innovation diffusion

Goal: The goal of IRPact is to develop a flexible and generic innovation-diffusion ABM (agent-based modelling) framework, based on requirements derived from a literature analysis. The aim of IRPact is to allow for modeling a large number of application contexts and questions of interest.
It provides a formal model (framework) as well as a software implementation in order to assist modelers with a basic infrastructure for their own research.
Conceptually it is thought to be part of the IRPsim (https://irpsim.uni-leipzig.de), with the vision to bring together rational approaches and cognitive modeling in an integrated approach within the context of sustainable energy markets.

Muhammad Indra Al Irsyad Member since: Wed, Nov 22, 2017 at 08:18 AM Full Member

Master degree, PhD candidate

My research examines the most effective and efficient policies for renewable energy development using an approach that integrates input-output analysis, life cycle analysis, econometric, and agent-based modelling to estimate the impacts of the policies to economic, emission, extracted materials, renewable energy capacity and social acceptance.

Tuong Manh Vu Member since: Wed, May 16, 2018 at 12:11 PM

I received my BSc, MSc, and PhD from the University of Nottingham. My PhD focuses on the Agent-Based Modelling and Simulation (ABMS) of Public Goods Game (PGG) in Economics. In my thesis, a development framework was developed using software-engineering methods to provide a structured approach to the development process of agent-based social simulations. Also as a case study, the framework was used to design and implement a simulation of PGG in the continuous-time setting which is rarely considered in Economics.

In 2017, I joined international, inter-disciplinary project CASCADE (Calibrated Agent Simulations for Combined Analysis of Drinking Etiologies) to further pursue my research interest in strategic modelling and simulation of human-centred complex systems. CASCADE, funded by the US National Institutes of Health (NIH), aims to develop agent-based models and systems-based models of the UK and US populations for the sequential and linked purposes of testing theories of alcohol use behaviors, predicting population alcohol use patterns, predicting population-level alcohol outcomes and evaluating the impacts of policy interventions on alcohol use patterns and harmful outcomes.

Etienne DELAY Member since: Thu, Oct 04, 2018 at 07:07 AM Full Member

Ph.D., Geography, Limoges univerity

To tackle the scientific challenges proposed by landscape dynamics and cooperation processes, I have developed a research methodology based on field work and companion modelling (ComMod) combined with the formalisation of the observed processes and agents based models.
This approach offers the possibility to understand : spatial, social, cultural and / or economic conditions that take place on territories, and to provide prospective scenarios.
These methods have been applied in various contexts: steep slope vineyards landscapes (2011), water resource management cooperation (2015), vegetation cover in dry climate (2017). The established research networks are still active through sustained collaborations and activities.

My technical expertise grew and evolved through investment in several workgroups: MAPS Team (Modelling Applied to Space Phenomena), OSGeo (president of the OSGeo’s French chapter between 2013 and 2016, member of the OSGeo-international chapter since 2015), various initiatives around modelling, exploration and sensibility analysis of spatial patterns behaviours, and more generally in Free Software communities.

I am interested in the socio-environmental conditions for the emergence of cooperation and mutual aid in social systems and mainly with regard to renewable resources. I consider in this context that Commons are a spatial manifestation of mutual aid.
From a technical point of view, I am very interested in the questions of model exploration (HPC), which led me to integrate the OpenMole community and to contribute to discussions about heuristic exploration.

Jagoda Anna Kaszowska Member since: Tue, Mar 05, 2019 at 03:10 PM Full Member

Ph.D., Finance

Postdoctoral researcher at Institute of Economics, Polish Academy of Sciences and in Macroprudential Research Division at National Bank of Poland. She graduated in Mathematics (Jagiellonian University, Poland) and in Economics (University of Alcala, Spain). In 2017 she obtained Fulbright Advanced Research Award. In the United States, she carried out research on systemic risk and complex systems. Her doctoral dissertation was about the measurement and modeling of systemic risk using simulation methods and complex systems approach (the results to be published by Palgrave Macmillan US). Previously, she gained experience on agent-based modeling while working with Juan Luis Santos on the European Commission FP 7 MOSIPS project (http://www.mosips.eu/).

Mathematics, complex systems, financial modeling, agent-based modeling, econometrics, macroprudential policies, systemic risk, cental banking

Kenneth Aiello Member since: Thu, Jan 23, 2020 at 04:14 PM Full Member

Ph.D., Biology and Society, Arizona State University, B.S., Sociology, Arizona State University,, B.S., Biology, Arizona State University

Kenneth D. Aiello is a postdoctoral research scholar with the Global BioSocial Complexity Initiative at ASU. Kenneth’s research contributes to cross disciplinary conversations on how historical developments in biological, social, and cultural knowledge systems are governed by processes that transform the structure, dynamics, and function of complex systems. Applying computational historical analysis and epistemology to question what scientific knowledge is and how we can analyze changes in knowledge, he uses text analysis, social network analysis, and machine learning to measure similarities and differences between the knowledge claims of individual agents and groups. His work builds on how to assess contested knowledge claims and measure the evolution of knowledge across complex systems and multiple dimensions of scale. This approach also engages in dynamic new debates about global and local structures of knowledge shaped by technological innovation within microbiology related to public policy, shrinking resources given to biomedical ideas as opposed to “translation”, and the ethics of scientific discovery. Using interdisciplinary methods for understanding historical content and context rich narratives contributes to understanding new domains and major transitions in science and provides a richer understanding of how knowledge emerges.

Elise Diva Member since: Sun, Jan 10, 2021 at 11:21 PM

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!

Rifqi Jalu Pramudita Member since: Tue, Apr 20, 2021 at 12:04 AM Full Member

Bachelor, Operational Management, Indonesia University of Education, Master, Logistics and Supply Chain Management, Institut Teknologi Sepuluh Nopember

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.

Displaying 10 of 27 results approach clear search

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