Utility Maximizing Design

Efficient design for maximized performance


The general framework I have formulated, Utility Maximizing Design (UMD), enables this principled design. The input of a UMD problem includes an initial environment, a description of agents (human users or artificial autonomous agents) that may be active within it, and a set of applicable design modifications. The challenge is to efficiently search through the typically large space of design options for a valid solution that maximizes a targeted objective, expressed via some utility measure. My work over the past few years has focused on developing different special cases of UMD, that vary in three ways: their targeted utility; the approaches that can be applied to find the optimal design solution; and the real world applications to which these settings correspond. The importance of this work is both theoretical, namely the development of principled design tools, and practical. My current research investigates the use of design to enhance multi-robot and human-robot collaboration

Have a look at my publication page to see the recent publications on UMD

Check out ROBIS system we are working on to support UMD for robotics 



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