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.
MY research aims to give artists better 3D references and scene reconstructions which can be directly fed into the creative pipeline. This is motivated by increasing public demand for detailed, complex 3D worlds and the resulting demand this places on world design artists.
This project lookings at developing acquisition and modelling technologies that provide more than just a visual reference: in the context of this project, visual acquisition and reconstruction methods shall be developed that provide richer, three-dimensional references, and that ultimately yield scene reconstructions that can directly be fed into the content creation pipeline. The project will focus on natural environments (as opposed to urban scenes) and may combine multi-spectral imaging, wide-baseline stereo reconstruction and semantic scene analysis to obtain approximate procedural representations of natural scenes.
My research is focused on understanding the importance of spatial and temporal environmental variability on communities and populations. The key question I aim to address is how the anthropogenic impacts, such as disturbances of individual animals or changed landscape heterogeneity associated with climate changes, influence the persistence of species. The harbour porpoise is an example of a species that is influenced by anthropogenic disturbances, and much of my research has focused on how the Danish porpoise populations are influenced by noise from offshore constructions. I use a wide range of modelling tools to assess the relative importance of different sources of environmental variation, including individual-based/agent based models, spatial statistics, and classical population models. This involves development of computer programs in R and NetLogo. In addition to my own research I currently supervise three PhD students and participate in the management of Department of Bioscience at Aarhus University.
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.
Angelos Chliaoutakis received his PhD in Electronic & Computer Engineering in 2020 at Technical University of Crete (TUC), Greece. During 2005-2020 he was a research assistant at the Intelligent Systems Laboratory of TUC, participating in several research projects associated with NLP, semantic similarity and ontology based information systems. Since 2010 he is also a research assistant at the Laboratory of Geophysical - Satellite Remote Sensing and Archaeo-environment (GeoSat ReSeArch Lab) of the Institute for Mediterranean Studies of Foundation for Research and Technology (IMS-FORTH), were he is involved in various research projects related to the full-stack development of Geographical Information Systems (GIS), web-based GIS applications and Geoinformatics in the cultural and archaeological domain. This ultimately transformed his interest and research direction towards computational archaeology, in particular, agent-based modeling and simulation, while intertwining ideas and approaches from Artificial Intelligence, Multi-agent Systems and GIS.
Research activities range between Computer Science, Information Systems and Natural Language Processing (NLP), Agent-based modeling/simulation (ABM), Artificial Intelligence (AI) and Multi-Agent Systems (MAS) and Geographical Information Science (GIScience).
performance of urban water service provision, high levels of inequities and inefficiency persist. In terms of water distribution and cost, these undesirable patterns have a high impact on peri-urban areas usually populated by marginalized and poor populations. The high levels of Non-Revenue Water (NRW), together with the existence of corrupt practices and mismanagement of water utilities, remain a highly controversial issue.
This situation confronts rent-seeking theory directly, explaining the performance-corruption relationship (Repetto, 1986). The presumption is that low performance in water supply service provision results from corruption because rent-seeking occurs. Hence, the implementation of performance-oriented reforms in the water supply sector, such as regulation or private sector participation, will reduce corruption, increasing the efficiency of water service provision. Nevertheless, latest evidence shows that “key elements of good political governance have a positive effect on the access to water services in developing countries. In turn, private sector participation has little influence other than increasing internal efficiency of water providers” (Krausse, 2009).
Indeed the relation between governance, corruption and performance seems to be more complex than theory wants to acknowledge. It must be reviewed further than a simple cause-effect relationship. It appears that poor management of water utilities, evidenced by high levels of NRW, justifies new investments. Such practices can be encouraged by an “opportunistic management”, whilst at the same time maintaining an influential “hydrocratic elite” in the sphere of water control.
The present research proposal aims to understand the relation between mismanagement and corruption of water control practices in water supply service provision. The research examines how this relationship affects the performance of water service provision and relates to water supply governance models at municipal peri-urban level in three African countries.
To understand the mismanagement-corruption relationship, we look at different case studies of water supply service provision in Senegal, Ghana and Kenya. Each case represents a different governance model in terms of management practices, institutional and organizational settings, and the actors in place, which affects the performance of water service provision in terms of allocative efficiency and access to water (equity). Whether regulation, decentralization and private sector participation constitute possible ways to reduce corruption is examined in the context of water sector reform.
In a second step, we propose a theoretical model based on Agent Based Modelling (ABM) (Pahl-Wostl, 2007) to reproduce complex social networks under a Socio-Ecological System (SES) framework approach. The model will allow us to test whether collaborative governance in the form of collective action in a participatory and negotiated decision-making process for water control, can reduce corruption and increase performance.
The present research benefits from the project “Transparency and Integrity in Service Delivery in Sub-Saharan Africa”. This project, carried out by Transparency International (TI) in 8 Sub-Saharan countries, aims to increase access to education, health and water by improving transparency and integrity in basic service delivery. The proposal retains focus on Senegal, Ghana and Kenya in the water sector.
Key words: water control, mismanagement, corruption, performance, collaborative governance, modelling, collective action, negotiation, participation
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.
Eric Kameni holds a Ph.D. in Computer Science option modeling and application from the Radboud University of Nijmegen in the Netherlands, after a Bachelor’s Degree in Computer Science in Application Development and a Diploma in Master’s degree with Thesis in Computer Science on “modeling the diffusion of trust in social networks” at the University of Yaoundé I in Cameroon. My doctoral thesis focused on developing a model-based development approach for designing ICT-based solutions to solve environmental problems (Natural Model based Design in Context (NMDC)).
The particular focus of the research is the development of a spatial and Agent-Based Model to capture the motivations underlying the decision making of the various actors towards the investments in the quality of land and institutions, or other aspects of land use change. Inductive models (GIS and statistical based) can extrapolate existing land use patterns in time but cannot include actors decisions, learning and responses to new phenomena, e.g. new crops or soil conservation techniques. Therefore, more deductive (‘theory-driven’) approaches need to be used to complement the inductive (‘data-driven’) methods for a full grip on transition processes. Agent-Based Modeling is suitable for this work, in view of the number and types of actors (farmer, sedentary and transhumant herders, gender, ethnicity, wealth, local and supra-local) involved in land use and management. NetLogo framework could be use to facilitate modeling because it portray some desirable characteristics (agent based and spatially explicit). The model develop should provide social and anthropological insights in how farmers work and learn.
Name: Dr. Julia Kasmire
Position: Post-doctoral Research Fellow
Where: UK Data Services and Cathie Marsh Institute at the University of Manchester.
2004 - BA in Linguistics from the University of California in Santa Cruz, including college honours, departmental honours and one year of study at the University of Barcelona.
2008 - MSc in the Evolution of Language and Cognition from the University of Edinburgh, with a thesis on the effects of various common simulated population features used when modelling language learning agents.
2015 - PhD from Faculty of Technology, Policy and Management at the Delft University of Technology under the supervision of Prof. dr. ig. Margot Wijnen, Prof. dr. ig. Gerard P.J. Dijkema, and Dr. ig. Igor Nikolic. My PhD thesis and propositions can be found online, as are my publications and PhD research projects (most of which addressed how to study transitions to sustainability in the Dutch horticultural sector from a computational social science and complex adaptive systems perspective).
Many of the NetLogo models I that built or used can be found here on my CoMSES/OpenABM pages.
My ResearchGate profile and my Academia.org profile provide additional context and outputs of my work, including some data sets, analytical resources and research skills endorsements.
My LinkedIn profile contains additional insights into my education and experience as well as skills and knowledge endorsements.
I try to use Twitter to share what is happening with my research and to keep abreast of interesting discussions on complexity, chaos, artificial intelligence, evolution and some other research topics of interest.
You can find my SCOPUS profile and my ORCID profile as well.
Complex adaptive systems, sustainability, evolution, computational social science, data science, empirical computer science, industrial regeneration, artificial intelligence