Geospatial Agents, Agents everywhere! (Sengupta & Sieber, 2007)

This paper gave a comprehensive overview of AI, agents, the role of these in GIScience. I found in many ways this overview brought up topics from the ‘GIS: Tool or Science’ debate, as the paper seemed to bring up AI a lot, when the real topic at hand were agents possibly due to the instant intrigue AI gets from many academic circles outside of geography. Additionally, the disaggregation of agents being either ALGAs or SGAs teases the question of whether agents transcend into their own field or are simply a large subset of GIScience.

The actual uses of agents, for which I was very unfamiliar to prior to this reading, are actually fascinating. Geospatial agents truly capture all aspects of geography (urban planning for urban sprawl modeling, LULC classifications, animal migrations, etc.) and have the ability to not only aid analyze geospatial data with SGAs, though even collect virtual data in the form of ALGAs. Although ALGAs resemble traditional AI and sci-fi, I find the use of SGAs very interesting for the possible near future. The ability to seamlessly work with the plethora of GIS data formats, as well as eliminate age old issues such as the Modifiable Arial Unit Problem and scale would be tremendous strides in GIScience. However, as someone who would like to work in a GIS field later, I also find this troubling as it removes from the human element of GIScience, in that the human knows these things and inputs them into the machine. If the machine does all the work, it seems GIS analysts could be computer techs rather than scientists quite easily.

Currently however, with the examples provided by Rodrigues and Raper (1999) SGAs currently come in the forms of (1) Personal agents (which could be spiders/crawlers), (2) assisting users in their GIS environment (easily done in Python or Bash scripts), (3)helping users find GIS data online (which exist in extensive GIS data repositories), and (4) assisting in decision-making collaborative spatial tasks (which could be seen as modeling in the cases provided on urban sprawl). So far these seem quite attainable, and it will be interesting to see the future uses/advances in geospatial agents, which sentient or not seem like they will have a large role to play in the GIScience future.


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