Low Complexity Control Policy Synthesis for Embodied Computation in Synthetic Cells
| Title: | Low Complexity Control Policy Synthesis for Embodied Computation in Synthetic Cells |
|---|---|
| Publication Type: | Conference Paper |
| Year of Publication: | 2018 |
| Authors: | A. Pervan, and T. D. Murphey |
| Conference Name: | Workshop on the Algorithmic Foundations of Robotics (WAFR) |
| Abstract: | As robots become more capable, they also become more complicated- either in terms of their physical bodies or their control architecture, or both. An iterative algorithm is introduced to compute feasible control policies that achieve a desired objective while maintaining a low level of design complexity (quantified using a measure of graph entropy) and a high level of task em- bodiment (evaluated by analyzing the Kullback-Leibler divergence between physical executions of the robot and those of an idealized system). When the resulting control policy is sufficiently capable, it is projected onto a set of sensor states. The result is a simple, physically-realizable design that is representative of both the control policy and the physical body. This method is demonstrated by computationally optimizing a simulated synthetic cell. |
PDF: 2018WAFRPeMu_0.pdf
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