@article {16543,
	title = {Automated design of distributed control rules for the self-assembly of prespecified artificial structures},
	journal = {Robotics and Autonomous Systems},
	volume = {56},
	year = {2008},
	month = {2008/04/30/},
	pages = {334 - 359},
	abstract = {The self-assembly problem involves the design of agent-level control rules that will cause the agents to form some desired, target structure, subject to environmental constraints. This paper describes a fully automated rule generation procedure that allows structures to successfully self-assemble in a simulated environment with constrained, continuous motion. This environment implicitly imposes ordering constraints on the self-assembly process, where certain parts of the target structure must be assembled before others, and where it may be necessary to assemble (and subsequently disassemble) temporary structures such as staircases. A provably correct methodology is presented for computing a partial order on the self-assembly process, and for generating rules that enforce this order at runtime. The assembly and disassembly of structures is achieved by generating another set of rules, which are inspired by construction behavior among certain species of social insects. Computational experiments verify the effectiveness of the approach on a diverse set of target structures.},
	keywords = {Collective problem solving, Coordination, Self-assembly, Stigmergy, Swarm intelligence},
	isbn = {0921-8890},
	doi = {10.1016/j.robot.2007.08.006},
	url = {http://www.sciencedirect.com/science/article/pii/S092188900700111X},
	author = {Grushin,Alexander and Reggia, James A.}
}
@conference {17361,
	title = {Snap-together visualization: a user interface for coordinating visualizations via relational schemata},
	booktitle = {Proceedings of the working conference on Advanced visual interfaces},
	series = {AVI {\textquoteright}00},
	year = {2000},
	month = {2000///},
	pages = {128 - 135},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Multiple coordinated visualizations enable users to rapidly explore complex information. However, users often need unforeseen combinations of coordinated visualizations that are appropriate for their data. Snap-Together Visualization enables data users to rapidly and dynamically mix and match visualizations and coordinations to construct custom exploration interfaces without programming. Snap{\textquoteright}s conceptual model is based on the relational database model. Users load relations into visualizations then coordinate them based on the relational joins between them. Users can create different types of coordinations such as: brushing, drill down, overview and detail view, and synchronized scrolling. Visualization developers can make their independent visualizations snap-able with a simple API.Evaluation of Snap revealed benefits, cognitive issues, and usability concerns. Data savvy users were very capable and thrilled to rapidly construct powerful coordinated visualizations. A snapped overview and detail-view coordination improved user performance by 30-80\%, depending on task.
},
	keywords = {Coordination, Information Visualization, multiple views, relational database, tight coupling, user interface, user study},
	isbn = {1-58113-252-2},
	doi = {10.1145/345513.345282},
	url = {http://doi.acm.org/10.1145/345513.345282},
	author = {North,Chris and Shneiderman, Ben}
}
