The Mid-Century Showroom: Knoll, Herman Miller and the Retail Exhibition of Modern American Design

Although occasionally illustrated and referenced in contemporary histories of modern furniture and design, there is surprisingly little critical discussion or consideration of the role of the showroom in the promotion and dissemination of modern design during the mid-twentieth century. In these years, when the American lifestyle was popularly articulated and forcefully propagandized, the furniture showroom served as a principle site of professional and public indoctrination. Appropriating display techniques from modern exhibition design to showcase the American lifestyle as an abstracted, spatially integrated art form, the showroom provided an unencumbered landscape ideally suited to camera’s lens and the public’s imagination. Leading modern American furniture manufacturers, such as Herman Miller and Knoll Associates collaborated with major cultural institutions as well as department stores and retailers to maximize exposure and consumer demand for their products. Through such integrated marketing and merchandising strategies, showrooms also contributed to the broader social project to educate American consumers about modern design and the advantages of modern living. Related to the many model home programs and “good design” exhibitions of the 1950s, the furniture showroom occupies a unique place within the history and discourse of the postwar era. The peculiarities of the furniture showroom and its position as a point of intersection between the trade and the consumer, the commercial and the cultural, and the aesthetic and the ideological form the focus of this study.

Deploy and search strategy for multi-agent systems using Voronoi partitions

In this paper we analyze a deploy and search strategy for multi-agent systems. Mobile agents equipped with sensors carry out search operation in the search space. The lack of information about the search space is modeled as an uncertainty density distribution over the space, and is assumed to be known to the agents a priori. In each step, the agents deploy themselves in an optimal way so as to maximize per step reduction in the uncertainty density. We analyze the proposed strategy for convergence and spatial distributedness. The control law moving the agents has been analyzed for stability and convergence using LaSalle's invariance principle, and for spatial distributedness under a few realistic constraints on the control input such as constant speed, limit on maximum speed, and also sensor range limits. The simulation experiments show that the strategy successfully reduces the average uncertainty density below the required level.