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Rodolphe Buda Member since: Mon, Feb 04, 2013 at 10:47 AM

Doctor in Economic Science

Main Research Topics :
1) Agent-based Modeling (Communication between agents)
2) Economic and Econometric Algorithms and Software Development
3) Optimal International Trade Configuration

Adrian Groza Member since: Mon, Apr 29, 2013 at 12:10 PM

Phd in Computer Science

Flexible agent communication
Argumentation in multi-agent systems
Knowledge representation and reasoning
Ontologies for agents
Mediation and Dispute Resolution

Rikard Roitto Member since: Tue, Jul 23, 2013 at 10:33 AM

PhD in Religious Studies

Historical studies of Early Christianity. Simulations of social agents aids my interpretation of history.

Andrea Ceschi Member since: Mon, Jan 12, 2015 at 06:33 PM Full Member

Ph.D.

Senior (Tenure-Track) Assistant Professor in Work and Organizational Psychology (WOP) at the Human Sciences Department of Verona University. My expertise lies in organizational behavior, individual differences and decision-making at work, and social dynamics in the applied psychology field. In the field of fundamental research my studies explore the role of individual antecedents (e.g., Personality traits, Risk attitudes, etc.) in relation to classic I/O models (e.g., Job Demands-Resources model, Effort-Reward model, etc.). My applied research focuses on the development of interventions and policies for enhancing decision-making, and in turn well-being and job performance. Finally, in industrial research, my research aims to better integrate cognitive and behavioral theories (e.g., Theory of Planned Behavior, Prospect theory, etc.) for designing predictive models – based on agents – of social and organizational behaviors.

Talal Alsulaiman Member since: Fri, Feb 27, 2015 at 04:10 AM

Bachelor of Science in Systems Engineering, Master of Science in Industrial Engineering, Master of Science in Financial Engineering

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.

Andreas Angourakis Member since: Wed, Feb 03, 2016 at 04:01 PM

PhD in Archaeology (University of Barcelona), Master Degree in Prehistorical Archaeology (Autonomous University of Barcelona), Degree in Sociology (Autonomous University of Barcelona), Degree in Humanities (Autonomous University of Barcelona)

I am a computational archaeologist with a strong background in humanities and social sciences, specialising in simulating socioecological systems from the past.

My main concern has been to tackle meaningful theoretical questions about human behaviour and social institutions and their role in the biosphere, as documented by history and archaeology. My research focuses specifically on how social behaviour reflects long-term historical processes, especially those concerning food systems in past small-scale societies. Among the aspects investigated are competition for land use between sedentary farmers and mobile herders (Angourakis et al. 2014; 2017), cooperation for food storage (Angourakis et al. 2015), origins of agriculture and domestication of plants (Angourakis et al. 2022), the sustainability of subsistence strategies and resilience to climate change (Angourakis et al. 2020, 2022). He has also been actively involved in advancing data science applications in archaeology, such as multivariate statistics on archaeometric data (Angourakis et al. 2018) and the use of computer vision and machine learning to photographs of human remains (Graham et al. 2020).

As a side, but not less important interest, I had the opportunity to learn about video game development and engage with professionals in Creative Industries. In one collaborative initiative, I was able to combine my know-how in both video games and simulation models (\href{https://doi.org/10.1007/978-3-030-92843-8_15}{Szczepanska et al. 2022}).

  • Modeling human-plant interactions in the origin of agriculture: Multiparadigmatic modeling and simulation (ABM, System Dynamics) of the interaction between humans and plants during domestication.
  • Modeling cooperation in small-scale food economies: Agent-based modeling and simulation of the mechanisms involved in the emergence and disruption of cooperative behavior and institutions.
  • Models of resource metabolism: study of matter, information and energy flows in systems with living agents at all scales.
  • Modeling prehistoric hunting: modeling hunting at the scale of individuals to understand the immediate constraints of hunting as an ecological, economical and social activity.
  • Modeling the interaction between herding and farming in arid environments: Agent-based modeling and simulation of the mechanisms involved in the formation and change of agro-pastoral land use patterns (sedentary farming and mobile herding) in the arid Afro-Eurasia.
  • Models for games, games for models: Explore the intersection between modeling in Archaeology and game design, aiming to improve our understanding of the long-term implications of human behavior.

Eric Hammer Member since: Wed, Sep 14, 2016 at 06:07 PM

BS Logistics Pennsylvania State University, MS Economics George Mason University, PhD Candidate Economics George Mason University

My academic interests involve public choice and the development of social norms for cooperation in the marketplace and the behavior of voting blocks. Recent work looks at the emergence of property rights “norms” among zero intelligence agents in an evolutionary context, and the dynamics of legislative party creation in an environment of stochastically voting voters.

Carole Adam Member since: Fri, Feb 03, 2017 at 02:58 PM

PhD in Artificial Intelligence
  • Since 2010: Associate Professor in Artificial Intelligence at Grenoble-Alpes University. Topic: human behaviour modelling, with a particular focus on emotions, cognitive biases, and their interplay with decision-making; social simulations and serious games for raising awareness about natural disasters and sustainable development, or for increasing civil engagement in urban planning.
  • 2008-2010: postdoctoral research fellow at RMIT, Melbourne, Australia. Supervisor: Lin Padgham. Topic: interactive intelligent emotional toy.
  • 2007-2008: research engineer at Orange Labs, Lannion, France. Supervisor: Vincent Louis. Topic: institutional logic in JADE for agent-based B2B mediation.
  • 2007: PhD in AI from Toulouse University. Supervisors: Andreas Herzig and Dominique Longin. Topic: logical modelling of emotions in BDI for artificial agents.

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).

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.

Sylvie Geisendorf Member since: Fri, Oct 06, 2017 at 10:14 AM

Dr., Prof.

Topics:

Behavioural aspects of environmental problems: Use of evolutionary approaches to investigate how people react to environmental policy.
Resource scarcity
Climate-economic Models: Understand how economic agents think and decide about climate change and climate protection
Sustainable Development

Methods:

Agent-Based-Modeling
Genetic algorithms
Evolutionary economics
Behavioural economics
Ecological economics
Complexity Theory

Displaying 10 of 28 results agents clear search

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