@inproceedings{Berman_Nagpal_Halasz11,
	author = {Spring Berman and Radhika Nagpal and {\'{A}}d{\'{a}}m Hal{\'{a}}sz},
	title = {Optimization of stochastic strategies for spatially inhomogeneous robot swarms: a case study in commercial pollination},
	year = {2011},
	pages = {3923--3930},
	abstract = {We present a scalable approach to optimizing robot control policies for a target collective 
        behavior in a spatially inhomogeneous robotic swarm. The approach can incorporate robot feedback to maintain 
        system performance in an unknown environmental flow field. We consider systems in which the robots follow both 
        deterministic and random motion and transition stochastically between tasks. Our methodology is based on an 
        abstraction of the swarm to a macroscopic continuous model, whose dimensionality is independent of the population 
        size, that describes the expected time evolution of swarm subpopulations over a discretization of the environment. 
        We incorporate this model into a stochastic optimization method and map the optimized model parameters onto the robot 
        motion and task transition control policies to achieve a desired global objective. We illustrate our methodology with 
        a scenario in which the behaviors of a swarm of robotic bees are optimized for both uniform and nonuniform pollination of a 
        blueberry field, including in the presence of an unknown wind.},
	doi = {10.1109/IROS.2011.6094771},
	address = {San Francisco, CA, USA},
	month = {September~25--30,},
	booktitle = {Proceedings of the 2011 {IEEE}/{RSJ} International Conference on Intelligent Robots and Systems~({IROS})}
}