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A macroscopic probabilistic model of adaptive foraging in swarm robotics systems

Liu, Wenguo; Winfield, Alan F.T.


Wenguo Liu


In this paper, we extend a macroscopic probabilistic model of a swarm of foraging robots from the homogeneous to the heterogeneous case. In the swarm, each robot is capable of adjusting its searching time and resting time thresholds following the rules described in our previous paper [1]. In
order to model the difference between robots, private/public resting time and searching time thresholds
are introduced, a number of equations are then developed to work out the relationship between these private time thresholds and public time thresholds based on previously developed difference equations [2]. The extended macroscopic probabilistic model has been tested using the simulation tools Player/Stage. The results from the macroscopic probabilistic model match with those from the simulation with reasonable accuracy, not only in the final net energy of the swarm but also in the instantaneous
net energy. Although the model is specific to adaptive foraging, we believe the methodology can be extended to other systems in which the heterogeneity of the system is coupled with its time parameters.

Presentation Conference Type Conference Paper (unpublished)
Start Date Feb 11, 2009
Publication Date Feb 1, 2009
Peer Reviewed Not Peer Reviewed
APA6 Citation Liu, W., & Winfield, A. F. (2009, February). A macroscopic probabilistic model of adaptive foraging in swarm robotics systems. Paper presented at 6th Vienna International Conference on Mathematical Modelling, Vienna
Keywords swarm robotics, foracging macroscopic, probabilistic


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