Policy and Use of ABM-Based Gaming Essay
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Policy and Use of ABM-Based Gaming Essay
Discussion-1 Comment 75 words. Agent-based modeling (ABM) is increasingly being used as a tool for the spatial simulation of a wide variety of urban phenomena including: housing dynamics
- urban growth and residential location
- gentrification
- and traffic simulation
- At a more microscopic level, there are agent-based models that simulate pedestrians in urban centers
- and crowd congestion
- These applications demonstrate a growing interest in linking agents to actual places and with geographic data
Through the linking or coupling with geographical information systems (GIS) and agent-based models. This coupling allows agent-based modelers to simulate agents related to actual geographic locations and to think about how objects or agents and their aggregations interact and change in space and time. As agent-based models move evermore into the spatial domain, there is a need for new ways to explore, visualize and communicate such models especially to those who we seek to influence or where such models might inform decision makers. This has already been identified as one of the key challenges facing ABM . One potential way to visualize and communicate agent-based models is to utilize the third dimension using advances in computer hardware, software and networked communication. This third dimension is rarely ventured into academic agent-based models.
We start by describing relevant features of ABM, emphasizing the particular way of thinking that is embodied in the method and the benefits of that framing. The paper then discusses three challenges that are particularly salient for public health researchers who wish to represent human behavior in ABMs, such as researchers interested in non-communicable diseases, and how these challenges might be overcome. These challenges are: appropriately representing behavior mechanisms, obtaining data to calibrate those mechanisms and validate the model, and developing the skills .
References
AT Crooks ( September , 2015) Advances and Techniques for Building 3D agent-based retrieved form : https://pdfs.semanticscholar.org/4172/1147e060b896305353e34b9438643491bdd6.pdf
J Badham (May , 2018) Developing agent -based models of complex health behavior retrieved from : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6284360/
Discussion-2 Comment 75 words.
Visualization for Policy Making
ABM-Based Gaming is an advantage and emerging approach that includes the 3D city modeling concept. This provides a digital model for an urban environment that includes a 3D geometry model for smart city construction (Janssen, Wimmer & Deljoo, 2015). This visualization technique is used for planning and environmental analysis of developing smart cities. In ABM-Based Gaming, 3D modeling is a part of spatial data infrastructure that analysis the thermal emission of the building. It provides the spectrum with visualization capabilities that helps in monitoring the vertical growth of the smart city.
Policy and Use of ABM-Based Gaming
ABM-Based Gaming provides a network connection with a simple rule that is used for programming elements of a smart city. The implementation of the concept provides open possibilities for intruding on new ideas in the market of a smart city. The simulation is helpful in providing experiments that can help in demonstrating an option for increasing the information stream. This includes the adoption percentage for the development of a smart city. This simulation looks for the suggestion that can help in targeting the option that is linked with making strategies (Janssen, Wimmer & Deljoo, 2015). ABM provides the possibilities for making various experiments for exploring conditions that can help in building a social system for a smart city. This allows in exploring social interaction and helps in identifying the entire key for the development of a smart city. 3D city modeling is sued for exploring the possibilities with management strategies that can help in performing are the different conditions in constriction of a smart city.
Data for Policy
The concept of Big Data is implemented in designing and storing the information of a smart city. The data is generated with the collection of information. A chi card is used for the recognition of data. RFID tags are used for sending the geographical location of data to a central monitoring system for the identification of areas in the smart city.
Reference
Janssen, M., Wimmer, M. A., & Deljoo, A. (Eds.). (2015). Policy practice and digital science: Integrating complex systems, social simulation and public administration in policy research (Vol. 10). Berlin, Germany: Springer
Discussion-3 Comment 75 words.
In this assignment, I would like to introduce a policy which would be helpful in the visualization for an ABM-based gaming simulation. In that case, the policy that I would like to generate is one which would make it easier for people to make use of visual decision support so that the complex systems could be more useful. Visual decision support is a tool which makes bulk and complex pieces of data easier to understand and therefore decisions could be made more efficiently and faster. Complex systems on the other hand are systems that have got a behavior that does not enable them to be easily modeled due to dependencies, competition, relationships or any other interaction between systems and their environment. When these two are combined and used as one, it would be easier to maintain and even improve the SmartCity scenario which aims to make cities evolve (Shaw J., 2015).
Therefore, the two concepts could work together perfectly well to achieve a better goal. I would use these two in the following way. Since in order to create visualization for an ABM-based on gaming simulation would require a very complicated system, I would employ the concepts of visual analytics to better understand the data that is needed. Since a simulation game normally wants to duplicate various activities from the real world which introduces complexity, the systems would very much be complex (Shaw J., 2015). Using the visual analytics to understand better the information needed, applying them to this task would be a good way to make the gaming simulation simpler and able to be run.
References:
Shaw J. (2015). INFORMATION TECHNOLOGY IN A GLOBAL ECONOMY. MANAGEMENT OF COMPLEX SYSTEMS: TOWARD AGENT-BASED GAMING FOR POLICY.
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