Displaying 10 of 54 results for "Roberto Cesar Betini" clear search
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.
In my research I focus on understanding human behaviour in group(s) as a part of a complex (social) system. My research can be characterised by the overall question: ‘How does group or collective behaviour arise or change given its social and physical context?‘ More specifically, I have engaged with: ‘How is (individual) human behaviour affected by being in a crowd?’, ‘Why do some groups (cooperatively) use their resources sustainably, whereas others do not?‘, ‘What is the role of (often implicit simplistic) assumptions regarding human behaviour for science and/or management?’
To address these questions, I use computational simulations to integrate and reflect synthesised knowledge from literature, empirics and experts. Models, simulation and data analysis are my tools for gaining a deeper understanding of the mechanisms underlying such systems. More specifically, I work with agent-based modelling (ABM), simulation experiments and data analysis of large datasets. Apart from crowd modelling and social-ecological modelling, I also develop methodological tools to analyse social simulation data and combining ABM with other methods, such as behavioural experiments.
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.
I am Colombian with passion for social impact. I believe that change starts at the individual, community, local and then global level. I have set my goal in making a better experience to whatever challenges I encounter and monetary systems and governance models is what concerns me at the time.
In my path to understanding and reflecting about these issues I have found my way through “Reflexive Modeling”. Models are just limited abstractions of reality and is part of our job as researchers to dig in the stories behind our models and learn to engage in a dialogue between both worlds.
Technology empowers us to act locally, autonomously and in decentralized ways and my research objective is to, in a global context, find ways to govern, communicate and scale the impact of alternative monetary models. This with a special focus on achieving a more inclusive and community owned financial system.
As a Ph.D. fellow for the Agenda 2030 Graduate School, I expect to identify challenges and conflicting elements in the sustainability agenda, contribute with new perspectives, and create solutions for the challenges ahead
I am currently enrolled as a graduate student at UC3M, working towards a MS degree in Computational and Applied Mathematics. Upon completing my current program, my intention is to further my education in Applied Economics, with a specific focus on the intersection of Climate and Development Economics.
My research pursuits center around investigating the impacts of climate change on developing nations. Additionally, I am interested in studying the repercussions of fast fashion consumption, examining its effects on working conditions, the environment, and the overall well-being of individuals in the countries where these garments are manufactured. In my ongoing master’s thesis, I employ Agent-Based Modeling to simulate the attitudes of individual consumers towards fast fashion. The model captures behavioral shifts influenced by peers, social media, and governmental factors. This research aligns with my broader interests in comprehending public perspectives on global matters, underscoring the crucial influence of individual attitudes in confronting and finding solutions to these challenges.
Development Economics, Environmental Economics, Sustainability, Environment, Climate change, Climate justice, Energy, Clean Energy, Renewable Energy, Complex systems
The Global Resource Observatory (GRO)
The Global Resource Observatory is largest single research project being undertaken at the GSI, it investigates how the scarcity of finite resources will impact global social and political fragility in the short term. The ambitious three year project, funded by the Dawe Charitable Trust, will enable short term decision making to account for ecological and financial constraints of a finite planet.
GRO will include an open source multidimensional model able to quantify the likely short term interactions of the human economy with the carrying capacity of the planet and key scarce resources. The model will enable exploration of the complex interconnections between the resource availability and human development, and provides projections over the next 5 years.
Data and scenarios will be geographically mapped to show the current and future balance and distribution of resources across and within countries. The GRO tool will, for the first time, enable the widespread integration of the implications of depleting key resource into all levels of policy and business decision-making.
I am an agent-based simulation modeler and social scientist living near Cambridge, UK.
In recent years, I have developed supply chain models for Durham University (Department of Anthropology), epidemiological models for the Covid-19 pandemic, and agent-based land-use models with Geography PhD students at Cambridge University.
Previously, I spent three years at Ludwig-Maximillians University, Munich, working on Human-Environment Relations and Sustainability, and over two and a half years at Surrey University, working on Innovation with Nigel Gilbert in the Centre for Research in Social Simulation (CRESS). The project at Surrey resulted in a book in 2014, “Simulating Innovation: Computer-based Tools for Rethinking Innovation”. My PhD topic, modeling human agents who energise or de-energise each other in social interactions, drew upon the work of sociologist Randall Collins. My multi-disciplinary background includes degrees in Operational Research (MSc) and Philosophy (BA/MA).
I got hooked on agent-based modeling and complexity science some time around 2000, via the work of Brian Arthur, Stuart Kauffman, Robert Axelrod and Duncan Watts (no relation!).
As an agent-based modeler, I specialize in NetLogo. For data analysis, I use Excel/VBA, and R, and occasionally Python 3, and Octave / MatLab.
My recent interests include:
* conflict and the emergence of dominant groups (in collaboration with S. M. Amadae, University of Helsinki);
* simulating innovation / novelty, context-dependency, and the Frame Problem.
When not working on simulations, I’m probably talking Philosophy with one of the research seminars based in Cambridge. I have a particular interests when these meet my agent-based modeling interests, including:
* Social Epistemology / Collective Intelligence;
* Phenomenology / Frame Problem / Context / Post-Heideggerian A.I.;
* History of Cybernetics & Society.
If you’re based near Cambridge and have an idea for a modeling project, then, for the cost of a coffee / beer, I’m always willing to offer advice.
I obtained a PhD in database information theory from the University of the West of Scotland in 2015, and have been a researcher at the James Hutton Institute ever since. My areas of research are agent-based-modelling (ABM), data curation, effective use of infrastructure as a service (IaaS), and semantic information representation and extraction using formal structures such as computerised ontologies, relational databases and any other structured or semi-structured data representations. I primarily deal with social and agricultural models and was originally taken on in the role of knowledge engineer in order to create the ontology for the H2020 project, Green Lifestyles, Alternative Models and Upscaling Regional Sustainability (GLAMURS). Subsequent work, for the Scottish Government has involved the use of IaaS, more commonly referred to as the “cloud” to create rapidly deployable and cheap alternatives to in-house high-performance computing for both ABM and Geographical Information System models.
It is the mixture of skills and interests involving modelling, data organisation and computing infrastructure expertise that I believe will be highly apposite in the duties associated with being a member of the CoMSES executive. Moreover, prior to joining academia, I spent about 25 years as a developer in commercial IT, in the agricultural, entertainment and banking sectors, and feel that such practical experience can only benefit the CoMSES network.
Dr. Lilian Alessa, University of Idaho President’s Professor of Resilient Landscapes in the Landscape Architecture program, is also Co-Director of the University of Idaho Center for Resilient Communities. She conducts extensive research on human adaptation to environmental change through resilient design at landscape scales. Much of her work is funded by the National Science Foundation, including projects awarded the Arctic Observing Network, Intersections of Food, Energy and Water Systems (INFEWS) and the Dynamics of Coupled Natural Human Systems programs. Canadian-born and raised, Alessa received her degrees from the University of British Columbia. She also uses her expertise in social-ecological and technological systems science to develop ways to improve domestic resource security for community well-being, particularly through the incorporation of place-based knowledge. Her work through the Department of Homeland Security’s Center of Excellence, the Arctic Domain Awareness Center, involves developing social-technological methods to monitor and respond to critical environmental changes. Lil is a member of the National Science Foundation’s Advisory Committee for Environmental Research and Education and is on the Science, Technology and Education Advisory Committee for the National Ecological Observing Network (NEON). Professor Alessa also teaches a university landscape architecture capstone course: Resilient Landscapes with Professor Andrew Kliskey. Professor Alessa’s collaborative grant activity with Professor Andrew Kliskey, since coming to the university in 2013, exceeds 7 million USD to date. She has authored over a 100 publications and reports and has led the development of 2 federal climate resilience toolbox assessments, the Arctic Water Resources Vulnerability Index (AWRVI) and the Arctic Adaptation Exchange Portal (AAEP).
Displaying 10 of 54 results for "Roberto Cesar Betini" clear search