A Novel Ant Clustering Algorithm Based on Cellular Automata
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Small Robots Team Up to Tackle Large Tasks
IEEE Distributed Systems Online
Cellular ANTomata: Food-Finding and Maze-Threading
ICPP '08 Proceedings of the 2008 37th International Conference on Parallel Processing
The Pillars of Computation Theory: State, Encoding, Nondeterminism
The Pillars of Computation Theory: State, Encoding, Nondeterminism
ISPA'07 Proceedings of the 5th international conference on Parallel and Distributed Processing and Applications
Ant colony optimisation for vehicle traffic systems: applications and challenges
International Journal of Bio-Inspired Computation
| Hi-index | 0.00 |
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.