Displaying 9 of 249 results for 'Clint A Penick'
My broad research interests are in human-environmental interactions and land-use change. Specifically, I am interested in how people make land-use decisions, how those decisions modify the functioning of natural systems, and how those modifications feedback on human well-being, livelihoods, and subsequent land-use decisions. All of my research begins with a complex systems background with the aim of understanding the dynamics of human-environment interactions and their consequences for environmental and economic sustainability. Agent-based modeling is my primary tool of choice to understand human-environment interactions, but I also frequently use other land change modeling approaches (e.g., cellular automata, system dynamics, econometrics), spatial statistics, and GIS. I also have expertise in synthesis methods (e.g., meta-analysis) for bringing together leveraging disparate forms of social and environmental data to understand how specific cases (i.e., local) of land-use change contribute to and/or differ from broader-scale (i.e. regional or global) patterns of human-environment interactions and land change outcomes.
Hello,
My name is Roberto and I am a graduate student at The Pennsylvania State University. I am in the “Information Sciences - Cybersecurity and Information Assurance program”, through which I discovered my interest in ABM. I am conducting my capstone research project on how to make ABM more effective in the disaster recovery planning process of IT companies. I am currently looking for interview candidates to conduct my research. If you or anyone you know have experience using ABM for disaster recovery planning in IT or tech, please reach out!
I learned about ABM through the Intelligent Agents course at Penn State, where we modeled everything from terrorist attacks to social relationships. I was immediately interested in ABM due to the potential and capabilities that it provides in so many areas. I hope to make ABM more popular in IT disaster recovery planning through my research, while learning more about ABM myself.
Cyber security
Agent-Based Modeling
Information Technology
Disaster Recovery
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.
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).
Professor, School of Human Evolution & Social Change
Professor, School of Complex Adaptive Systems
Affiliate Professor, School of Earth and Space Exploration
Arizona State University
My interests center around long-term human ecology and landscape dynamics with ongoing projects in the Mediterranean (late Pleistocene through mid-Holocene) and recent work in the American Southwest (Holocene-Archaic). I’ve done fieldwork in Spain, Bosnia, and various locales in North America and have expertise in hunter/gatherer and early farming societies, geoarchaeology, lithic technology, and evolutionary theory, with an emphasis on human/environmental interaction, landscape dynamics, and techno-economic change.
Quantitative methods are critical to archaeological research, and socioecological sciences in general. They are an important focus of my research, especially emphasizing dynamic modeling, spatial technologies (including GIS and remote sensing), statistical analysis, and visualization. I am a member of the open source GRASS GIS international development team that is making cutting edge spatial technologies available to researchers and students around the world.
I am a spatial (GIS) agent-based modeler i.e. modeler that simulates the impact of various individual decisions on the environment. My work is mainly methodological i.e. I develop tools that make agent-based modeling (ABM) easier to do. I especially focus on developing tools that allow for evaluating various uncertainties in ABM. One of these uncertainties are the ways of quantifying agent decisions (i.e. the algorithmic representation of agent decision rules) for example to address the question of “How do the agents decide whether to grow crops or rather put land to fallow?”. One of the methods I developed focuses on representing residential developers’ risk perception for example to answer the question: “to what extent is the developer risk-taking and would be willing to build new houses targeted at high-income families (small market but big return on investment)?”. Other ABM uncertainties that I evaluate are various spatial inputs (e.g. different representations of soil erosion, different maps of environmental benefits from land conservation) and various demographics (i.e. are retired farmers more willing to put land to conservation?). The tools I develop are mostly used in (spatial) sensitivity analysis of ABM (quantitative, qualitative, and visual).
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’ve been building cyberinfrastructure and research software for computational social science and the study of complex adaptive systems at Arizona State University since 2006. Past and current projects include the Digital Archaeological Record, the Virtual Commons, the Social Ecological Systems Library, Synthesizing Knowledge of Past Environments (SKOPE), the Port of Mars, and CoMSES Net, where I serve as co-director and technical lead.
I also work to improve the state of open, transparent, reusable, and reproducible computational science as a Carpentries instructor and maintainer for the Plotting and Programming in Python and Good Enough Practices for Scientific Computing lessons, currently co-chair the Consortium of Scientific Software Registries and Repositories and Open Modeling Foundation Cyberinfrastructure Working Group, and serve on the DataCite Services and Technology Steering Group and CSDMS’s Basic Model Interface open source governance council.
My research interests include collective action, social ecological systems, large-scale software systems engineering, model componentization and coupling, and finding effective ways to promote and facilitate good software engineering practices for reusable, reproducible, and interoperable scientific computation.
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
Displaying 9 of 249 results for 'Clint A Penick'