Abstract
Ants provide an attractive metaphor for robots that “cooperate” to perform complex tasks. This paper is a step toward understanding the algorithmic concomitants of this metaphor, the strengths and weaknesses of ant-based computation models. We study the ability of finite-state ant-robots to scalably perform a simple path-planning task called parking, within fixed, geographically constrained environments (“factory floors”). This task: (1) has each ant head for its nearest corner of the floor and (2) has all ants within a corner organize into a maximally compact formation. Even without (digital analogues of) pheromones, many initial configurations of ants can park, including: (a) a single ant situated along an edge of the floor; (b) any assemblage of ants that begins with two designated adjacent ants. In contrast, a single ant in the middle of (even a one-dimensional) floor cannot park, even with the help of (volatile digital) pheromones.
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Rosenberg, A.L. (2010). Ants in Parking Lots. In: D’Ambra, P., Guarracino, M., Talia, D. (eds) Euro-Par 2010 - Parallel Processing. Euro-Par 2010. Lecture Notes in Computer Science, vol 6272. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15291-7_37
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DOI: https://doi.org/10.1007/978-3-642-15291-7_37
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