The latest outputs from researchers, alumni and friends at the UCL Centre for Advanced Spatial Analysis (CASA).
We just had a paper accepted in Advances in Complex Systems entitled “The Effect of In-group Favoritism on the Collective Behavior of Individuals’ Opinions.” In the paper we develop and an agent-based model to explore how individuals interact and how m…
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We just had a paper accepted in Advances in Complex Systems entitled “The Effect of In-group Favoritism on the Collective Behavior of Individuals’ Opinions.” In the paper we develop and an agent-based model to explore how individuals interact and how m…
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What now seems like a very long long time ago, when I was getting up to speed with Agent-based modeling and GIS, I came across a great edited book entitled “Dynamics in Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes”….
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What now seems like a very long long time ago, when I was getting up to speed with Agent-based modeling and GIS, I came across a great edited book entitled “Dynamics in Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes”….
Continue reading »
Do you like big data and geosimulation and wondering when to book flights or which sessions to attend at the forthcoming AAG Annual Meeting, If so, you might like our sessions entitled “Geosimulation and Big Data: A Marriage made in Heaven or Hel…
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Do you like big data and geosimulation and wondering when to book flights or which sessions to attend at the forthcoming AAG Annual Meeting, If so, you might like our sessions entitled “Geosimulation and Big Data: A Marriage made in Heaven or Hel…
Continue reading »
Chris Brunsdon and Alex Singleton recently edited a book entitled “Geocomputation: A Practical Primer“. The book covers a plethora of topics relating to geocomputation, and to quote from the website: “Chapters provide highly applied and practical discussions of:
- Visualization and exploratory spatial data analysis
- Space time modelling
- Spatial algorithms
- Spatial regression and statistics
- Enabling interactions through the use of neogeography ”
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| Representing the world as a series of layers of fixed and non-fixed objects (adapted from Benenson and Torrens, 2004). |
The chapter therefore introduces agent-based models to those interested in geocomputational methods, argues why such models should be used to study geographical problems before discussing how one can use GIS to create geographical explicit agent-based models. Through a series of examples we demonstrate how raster or vector spatial data can be used to model various aspects of our daily lives from that of the micro movement of pedestrians over seconds and minutes, to that of the macro patterns of urban growth over years and decades. By integrating spatial data and agent-based models at different spatial and temporal scales, such a modeling approach provides the flexibility to aid social scientists to explore the complex world that we inhabit.
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| A sample of application domains for spatial agent-based models discussed in the chapter. |
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| A simple example using MASON on how Agent-based models can be to used explore rush hour congestion: (A): Road and census data used for model inputs. (B) Zoomed in section of A with agents (red circles) moving towards Tyson’s Corner and causing traffic jams. |
Reference Cited:
Benenson, I. and Torrens, P.M. (2004), Geosimulation: Automata-Based Modelling of Urban Phenomena, John Wiley & Sons, London, UK.
Full Reference to Chapter:
Crooks, A.T. (2015), Agent-based Models and Geographical Information Systems, in Brunsdon, C. and Singleton, A. (eds.), Geocomputation: A Practical Primer, Sage, London, UK, pp. 63-77. (pdf)
Chris Brunsdon and Alex Singleton recently edited a book entitled “Geocomputation: A Practical Primer“. The book covers a plethora of topics relating to geocomputation, and to quote from the website: “Chapters provide highly applied and practical discussions of:
- Visualization and exploratory spatial data analysis
- Space time modelling
- Spatial algorithms
- Spatial regression and statistics
- Enabling interactions through the use of neogeography ”
|
| Representing the world as a series of layers of fixed and non-fixed objects (adapted from Benenson and Torrens, 2004). |
The chapter therefore introduces agent-based models to those interested in geocomputational methods, argues why such models should be used to study geographical problems before discussing how one can use GIS to create geographical explicit agent-based models. Through a series of examples we demonstrate how raster or vector spatial data can be used to model various aspects of our daily lives from that of the micro movement of pedestrians over seconds and minutes, to that of the macro patterns of urban growth over years and decades. By integrating spatial data and agent-based models at different spatial and temporal scales, such a modeling approach provides the flexibility to aid social scientists to explore the complex world that we inhabit.
|
| A sample of application domains for spatial agent-based models discussed in the chapter. |
|
| A simple example using MASON on how Agent-based models can be to used explore rush hour congestion: (A): Road and census data used for model inputs. (B) Zoomed in section of A with agents (red circles) moving towards Tyson’s Corner and causing traffic jams. |
Reference Cited:
Benenson, I. and Torrens, P.M. (2004), Geosimulation: Automata-Based Modelling of Urban Phenomena, John Wiley & Sons, London, UK.
Full Reference to Chapter:
Crooks, A.T. (2015), Agent-based Models and Geographical Information Systems, in Brunsdon, C. and Singleton, A. (eds.), Geocomputation: A Practical Primer, Sage, London, UK, pp. 63-77. (pdf)
You can download the code from here.
Continue reading »You can download the code from here.
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| Cholera transmission through the interaction of host and the environment |
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| Cholera dynamics when rainfall is introduced. |
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| Spatial spread of cholera over the course of a year. |
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| Study area |
“Cholera is an intestinal disease and is characterized by diarrhea and severe dehydration. While cholera has mainly been eliminated in regions that can provide clean water, adequate hygiene and proper sanitation; it remains a constant threat in many parts of Africa and Asia. Within this paper, we develop an agent-based model that explores the spread of cholera in the Dadaab refugee camp in Kenya. Poor sanitation and housing conditions contribute to frequent incidents of cholera outbreaks within this camp. We model the spread of cholera by explicitly representing the interaction between humans and their environment, and the spread of the epidemic using a Susceptible-Exposed-Infected-Recovered model. Results from the model show that the spread of cholera grows radially from contaminated water sources and seasonal rains can cause the emergence of cholera outbreaks. This modeling effort highlights the potential of agent-based modeling to explore the spread of cholera in a humanitarian context.”
Crooks, A.T. and Hailegiorgis, A.B. (2014), An Agent-based Modeling Approach Applied to the Spread of Cholera, Environmental Modelling and Software, 62: 164-177
DOI: 10.1016/j.envsoft.2014.08.027 (pdf)
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| Cholera transmission through the interaction of host and the environment |
|
| Cholera dynamics when rainfall is introduced. |
|
| Spatial spread of cholera over the course of a year. |
|
| Study area |
“Cholera is an intestinal disease and is characterized by diarrhea and severe dehydration. While cholera has mainly been eliminated in regions that can provide clean water, adequate hygiene and proper sanitation; it remains a constant threat in many parts of Africa and Asia. Within this paper, we develop an agent-based model that explores the spread of cholera in the Dadaab refugee camp in Kenya. Poor sanitation and housing conditions contribute to frequent incidents of cholera outbreaks within this camp. We model the spread of cholera by explicitly representing the interaction between humans and their environment, and the spread of the epidemic using a Susceptible-Exposed-Infected-Recovered model. Results from the model show that the spread of cholera grows radially from contaminated water sources and seasonal rains can cause the emergence of cholera outbreaks. This modeling effort highlights the potential of agent-based modeling to explore the spread of cholera in a humanitarian context.”
Crooks, A.T. and Hailegiorgis, A.B. (2014), An Agent-based Modeling Approach Applied to the Spread of Cholera, Environmental Modelling and Software, 62: 164-177
DOI: 10.1016/j.envsoft.2014.08.027 (pdf)
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Over the last few months we have been working on developing a agent-based model which explores the spread and containment of tuberculosis. Today is the first time that we show the model to a academic audience at the AAG Annual meeting. To give a sense …
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Over the last few months we have been working on developing a agent-based model which explores the spread and containment of tuberculosis. Today is the first time that we show the model to a academic audience at the AAG Annual meeting. To give a sense …
Continue reading »
Over the last few months we have been working on developing a agent-based model which explores the spread and containment of tuberculosis. Today is the first time that we show the model to a academic audience at the AAG Annual meeting. To give a sense …
Continue reading »
“(i) to contribute to the dissemination of the recent research and development of the use of information and communication technologies (ICT) in urban and spatial planning, trying to demonstrate their usability in planning processes through the presentation of relevant case studies, framed by their underlying theory; (ii) to give additional evidence to the fact that ICT are the privileged means to produce virtual cities and territories; and (iii) to make available, from a pedagogical standpoint, a group of illustrative reviews of the scientific production made by both academics and practitioners in the field.”
The book has 11 chapters which are grouped in several themes:
“first group focuses on the discussion over the use of ICT in spatial planning; the second group of contributions deals with urban modelling and simulation; the third group focuses on the use of different sensors to acquire information and model spatial processes; the fourth group focuses on the use of data to create more capable visualization tools; and the fifth group is about the use of virtual models to simulate real environments and plan and manage other aspects of the built environment such as energy.”
Cities provide homes for over half of the world’s population, and this proportion is expected to increase throughout the next century. The growth of cities raises many questions and challenges for urban planning including which cities and regions are most likely to grow, what the pattern of urban growth will be, and how the existing infrastructure will cope with such growth. One way to explore these types of questions is through the use of multi-agent systems (MAS) that are capable of modeling how individuals interact and how structures emerge through such interactions, in terms of both the social and physical environment of cities. Within this chapter, the authors focus on how MAS can lead to insights into urban problems and aid urban planning from the bottom up. They review MAS models that explore the growth of cities and regions, models that explore land-use patterns resulting from such growth along with the rise of slums. Furthermore, the authors demonstrate how MAS models can be used to model transportation and the changing demographics of cities. Through these examples the authors also demonstrate how this style of modeling can give insights into such issues that cannot be gleamed from other modeling methodologies. The chapter concludes with challenges and future research directions of MAS models with respect to capturing the dynamics of human behavior in urban planning.
Full Reference:
Continue reading »Crooks, A.T., Patel, A. and Wise, S. (2014), Multi-agent Systems for Urban Planning, in Pinto, N.N., Tenedório, J. Antunes A. P. and Roca, J. (eds.), Technologies for Urban and Spatial Planning: Virtual Cities and Territories, IGI Global, Hershey, PA, pp. 29-56. (pdf)
“(i) to contribute to the dissemination of the recent research and development of the use of information and communication technologies (ICT) in urban and spatial planning, trying to demonstrate their usability in planning processes through the presentation of relevant case studies, framed by their underlying theory; (ii) to give additional evidence to the fact that ICT are the privileged means to produce virtual cities and territories; and (iii) to make available, from a pedagogical standpoint, a group of illustrative reviews of the scientific production made by both academics and practitioners in the field.”
The book has 11 chapters which are grouped in several themes:
“first group focuses on the discussion over the use of ICT in spatial planning; the second group of contributions deals with urban modelling and simulation; the third group focuses on the use of different sensors to acquire information and model spatial processes; the fourth group focuses on the use of data to create more capable visualization tools; and the fifth group is about the use of virtual models to simulate real environments and plan and manage other aspects of the built environment such as energy.”
Cities provide homes for over half of the world’s population, and this proportion is expected to increase throughout the next century. The growth of cities raises many questions and challenges for urban planning including which cities and regions are most likely to grow, what the pattern of urban growth will be, and how the existing infrastructure will cope with such growth. One way to explore these types of questions is through the use of multi-agent systems (MAS) that are capable of modeling how individuals interact and how structures emerge through such interactions, in terms of both the social and physical environment of cities. Within this chapter, the authors focus on how MAS can lead to insights into urban problems and aid urban planning from the bottom up. They review MAS models that explore the growth of cities and regions, models that explore land-use patterns resulting from such growth along with the rise of slums. Furthermore, the authors demonstrate how MAS models can be used to model transportation and the changing demographics of cities. Through these examples the authors also demonstrate how this style of modeling can give insights into such issues that cannot be gleamed from other modeling methodologies. The chapter concludes with challenges and future research directions of MAS models with respect to capturing the dynamics of human behavior in urban planning.
Full Reference:
Continue reading »Crooks, A.T., Patel, A. and Wise, S. (2014), Multi-agent Systems for Urban Planning, in Pinto, N.N., Tenedório, J. Antunes A. P. and Roca, J. (eds.), Technologies for Urban and Spatial Planning: Virtual Cities and Territories, IGI Global, Hershey, PA, pp. 29-56. (pdf)
“(i) to contribute to the dissemination of the recent research and development of the use of information and communication technologies (ICT) in urban and spatial planning, trying to demonstrate their usability in planning processes through the presentation of relevant case studies, framed by their underlying theory; (ii) to give additional evidence to the fact that ICT are the privileged means to produce virtual cities and territories; and (iii) to make available, from a pedagogical standpoint, a group of illustrative reviews of the scientific production made by both academics and practitioners in the field.”
The book has 11 chapters which are grouped in several themes:
“first group focuses on the discussion over the use of ICT in spatial planning; the second group of contributions deals with urban modelling and simulation; the third group focuses on the use of different sensors to acquire information and model spatial processes; the fourth group focuses on the use of data to create more capable visualization tools; and the fifth group is about the use of virtual models to simulate real environments and plan and manage other aspects of the built environment such as energy.”
Cities provide homes for over half of the world’s population, and this proportion is expected to increase throughout the next century. The growth of cities raises many questions and challenges for urban planning including which cities and regions are most likely to grow, what the pattern of urban growth will be, and how the existing infrastructure will cope with such growth. One way to explore these types of questions is through the use of multi-agent systems (MAS) that are capable of modeling how individuals interact and how structures emerge through such interactions, in terms of both the social and physical environment of cities. Within this chapter, the authors focus on how MAS can lead to insights into urban problems and aid urban planning from the bottom up. They review MAS models that explore the growth of cities and regions, models that explore land-use patterns resulting from such growth along with the rise of slums. Furthermore, the authors demonstrate how MAS models can be used to model transportation and the changing demographics of cities. Through these examples the authors also demonstrate how this style of modeling can give insights into such issues that cannot be gleamed from other modeling methodologies. The chapter concludes with challenges and future research directions of MAS models with respect to capturing the dynamics of human behavior in urban planning.
Full Reference:
Continue reading »Crooks, A.T., Patel, A. and Wise, S. (2014), Multi-agent Systems for Urban Planning, in Pinto, N.N., Tenedório, J. Antunes A. P. and Roca, J. (eds.), Technologies for Urban and Spatial Planning: Virtual Cities and Territories, IGI Global, Hershey, PA, pp. 29-56. (pdf)
If you going to this years AAG, you might be interested in our Geosimulation Models sessions which will take place on Wednesday the 9th of April from 10am.
Session Description: Since the publication of Geosimulation in 2004, the use of Agent-based Modeling (ABM) and Cellular Automata (CA) under the umbrella of Geosimulation models within geographical systems have started to mature as methodologies to explore a wide range of geographical and more broadly social sciences problems facing society. The aim of these sessions is to bring together researchers utilizing geosimulation techniques (and associated methodologies) to discuss topics relating to: theory, technical issues and applications domains of ABM and CA within geographical systems.
If you going to this years AAG, you might be interested in our Geosimulation Models sessions which will take place on Wednesday the 9th of April from 10am.
Session Description: Since the publication of Geosimulation in 2004, the use of Agent-based Modeling (ABM) and Cellular Automata (CA) under the umbrella of Geosimulation models within geographical systems have started to mature as methodologies to explore a wide range of geographical and more broadly social sciences problems facing society. The aim of these sessions is to bring together researchers utilizing geosimulation techniques (and associated methodologies) to discuss topics relating to: theory, technical issues and applications domains of ABM and CA within geographical systems.
Readers of the blog might be interested in reading Josh Epstein’s new book “Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science” To quote from the publisher:”In this pioneering synthesis, Joshua Epstein introduces a new theoreti…
Continue reading »Readers of the blog might be interested in reading Josh Epstein’s new book “Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science” To quote from the publisher:”In this pioneering synthesis, Joshua Epstein introduces a new theoreti…
Continue reading »Readers of the blog might be interested in reading Josh Epstein’s new book “Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science” To quote from the publisher:”In this pioneering synthesis, Joshua Epstein introduces a new theoreti…
Continue reading »Model design is one of the most important stages of the development of any agent-based model. Get the design wrong and you might find yourself tied up in knots, battling against the structure of the project you defined months before. Get it right and you’ll leave yourself a extensible platform to develop into, allowing yourself …
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GEOSIMULATION MODELS DESCRIPTION OF THE SESSION(S) Since the publication of Geosimulation in 2004, the use of Agent-based Modeling (ABM) and Cellular Automata (CA) under the umbrella of Geosimulation models within geographical systems have started to…
Continue reading »
GEOSIMULATION MODELS DESCRIPTION OF THE SESSION(S) Since the publication of Geosimulation in 2004, the use of Agent-based Modeling (ABM) and Cellular Automata (CA) under the umbrella of Geosimulation models within geographical systems have started to…
Continue reading »
Following on from a previous post about the rise of civilizations. I thought it was worth blogging of another publication which I just came across in Environment and Planning A which demonstrates the utility of agent-based modeling for looking at urban systems by Denise Pumain and Lena Sanders. While I have blogged about the SimPop models before (here), which explore a systems of cities and how they evolve in space and time. In this recent paper the authors compare and contrast ABM with other styles of modeling. To quote from the paper:
“Agent-based models are increasingly used by urban specialists, supplanting the simulation models using differential equations which were more popular earlier. These models already made reference to the theories of self-organisation and to mechanisms of evolution not so far from those used today to describe the emergence of macroscopic properties or structures in a bottom-up process from interactions operating at the microlevel. Moreover there is less difference than often suggested in the literature between the two forms of modelling – differential equations and multi-agent models—in the way they integrate principles of urban theory. To test this assumption, we compare models made of systems of differential equations (Allen’s model firmly rooted in self-organisation theory and the model developed by Weidlich and Haag, affiliated to synergetic theory) with multi-agent models (SIMPOP family) designed to meet the same task: simulating the differentiated dynamics of urban entities over the medium to long term from their functional economic specialisation. We show that multi-agent systems are providing interesting solutions for the modelling method, because of their greater ability to simulate the emergence of geographical macro structures from different levels of interaction.”
Full Reference:
Pumain, D. and Sanders, L. (2013). Theoretical principles in interurban simulation models: a comparison. Environment and Planning A, 45(9), 2243-2260.
Continue reading »
Following on from a previous post about the rise of civilizations. I thought it was worth blogging of another publication which I just came across in Environment and Planning A which demonstrates the utility of agent-based modeling for looking at urban systems by Denise Pumain and Lena Sanders. While I have blogged about the SimPop models before (here), which explore a systems of cities and how they evolve in space and time. In this recent paper the authors compare and contrast ABM with other styles of modeling. To quote from the paper:
“Agent-based models are increasingly used by urban specialists, supplanting the simulation models using differential equations which were more popular earlier. These models already made reference to the theories of self-organisation and to mechanisms of evolution not so far from those used today to describe the emergence of macroscopic properties or structures in a bottom-up process from interactions operating at the microlevel. Moreover there is less difference than often suggested in the literature between the two forms of modelling – differential equations and multi-agent models—in the way they integrate principles of urban theory. To test this assumption, we compare models made of systems of differential equations (Allen’s model firmly rooted in self-organisation theory and the model developed by Weidlich and Haag, affiliated to synergetic theory) with multi-agent models (SIMPOP family) designed to meet the same task: simulating the differentiated dynamics of urban entities over the medium to long term from their functional economic specialisation. We show that multi-agent systems are providing interesting solutions for the modelling method, because of their greater ability to simulate the emergence of geographical macro structures from different levels of interaction.”
Full Reference:
Pumain, D. and Sanders, L. (2013). Theoretical principles in interurban simulation models: a comparison. Environment and Planning A, 45(9), 2243-2260.
Continue reading »
GEOSIMULATION MODELS DESCRIPTION OF THE SESSION(S) Since the publication of Geosimulation in 2004, the use of Agent-based Modeling (ABM) and Cellular Automata (CA) under the umbrella of Geosimulation models within geographical systems have started to m…
Continue reading »
GEOSIMULATION MODELS DESCRIPTION OF THE SESSION(S) Since the publication of Geosimulation in 2004, the use of Agent-based Modeling (ABM) and Cellular Automata (CA) under the umbrella of Geosimulation models within geographical systems have started to m…
Continue reading »
People interested in exploring the connections between land-use, livelihood strategies, and sustainability should check out Nicholas Magliocca from the Agent-Based Virtual Labs blog who has a new a paper entitled ” Exploring Agricultural Liveliho…
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People interested in exploring the connections between land-use, livelihood strategies, and sustainability should check out Nicholas Magliocca from the Agent-Based Virtual Labs blog who has a new a paper entitled ” Exploring Agricultural Liveliho…
Continue reading »
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| Original Overview, Design concepts, and Details (ODD) protocol (Source: Grimm et al., 2006). |
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| Extended ODD for describing human decisions in agent-based models – ODD + D (Source: Müller et al., 2013) |
Full references to the papers:
Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S., Huse, G., Huth, A., Jepsen, J., Jorgensen, C., Mooij, W., Muller, B., Pe’er, G., Piou, C., Railsback, S., Robbins, A., Robbins, M., Rossmanith, E., Ruger, N., Strand, E., Souissi, S., Stillman, R., Vabo, R., Visser, U. and Deangelis, D. (2006), ‘A Standard Protocol for Describing Individual-Based and Agent-Based Models‘, Ecological Modelling, 198(1-2): 115–126.
Müller, B., Bohn, F., Dreßler, G., Groeneveld, J., Klassert, C., Martin, R., Schlüter, M., Schulze, J., Weise, H. and Schwarz, N. (2013), ‘Describing Human Decisions in Agent-based Models – ODD + D, An Extension of the ODD Protocol‘, Environmental Modelling and Software, 48: 37-48.
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| Original Overview, Design concepts, and Details (ODD) protocol (Source: Grimm et al., 2006). |
|
| Extended ODD for describing human decisions in agent-based models – ODD + D (Source: Müller et al., 2013) |
Full references to the papers:
Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S., Huse, G., Huth, A., Jepsen, J., Jorgensen, C., Mooij, W., Muller, B., Pe’er, G., Piou, C., Railsback, S., Robbins, A., Robbins, M., Rossmanith, E., Ruger, N., Strand, E., Souissi, S., Stillman, R., Vabo, R., Visser, U. and Deangelis, D. (2006), ‘A Standard Protocol for Describing Individual-Based and Agent-Based Models‘, Ecological Modelling, 198(1-2): 115–126.
Müller, B., Bohn, F., Dreßler, G., Groeneveld, J., Klassert, C., Martin, R., Schlüter, M., Schulze, J., Weise, H. and Schwarz, N. (2013), ‘Describing Human Decisions in Agent-based Models – ODD + D, An Extension of the ODD Protocol‘, Environmental Modelling and Software, 48: 37-48.
Looking at frameworks and toolkits to easily create agent-based models, I recntly came across Modelling Agent systems based on Institutional Analysis (MAIA) framework via JASSS. The idea for MAIA is to lower the cost of implementing agent-based models….
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Looking at frameworks and toolkits to easily create agent-based models, I recntly came across Modelling Agent systems based on Institutional Analysis (MAIA) framework via JASSS. The idea for MAIA is to lower the cost of implementing agent-based models….
Continue reading »