Geospatial agents or AI agents? On Sieber and Sengupta, 2007

Sengupta and Sieber (2007) present an overview of geospatial agents and situate the concept within existing literature. The concept of an intelligent agent was completely new to me before reading this article. Despite the definitions provided, my lack of knowledge about AI made it difficult for me to grasp many of the concepts outlined in this paper.

This article provides the basis for geospatial agents as a distinct category of AI agents. After previous class discussions, I better understand the need for such an argument. By giving geospatial agents their own territory, distinct from that of AI agents, research agendas focusing on geospatial agents are legitimized and perhaps better funded. A review article like this, which works to define an emergent research area, is also incredibly beneficial as it allows researchers in the field to better situate their own work and draw from key bodies of literature. In this sense, working to define and contextualize a research domain can help drive further innovation in that domain.

Sengupta and Sieber outline two distinct types of geospatial agents: artificial life geospatial agents (ALGAs) and software geospatial agents (SGAs). As ALGAs are used in geosimulation to model movement in space, I understand the relevance of geography and spatial awareness. While SGAs are used to directly handle geospatial information, it is less clear to me how these types of agents are unique to geography. An SGA which has been programmed with information about spatial data models and geospatial issues may still not be intelligent about space itself. I believe that ALGAs are an example of a geospatial agent that is distinct from an AI agent, but I’m not convinced that the same can be said for SGAs.

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