Exploiting probabilistic knowledge under uncertain sensing for efficient robot behaviour

Robots must perform tasks efficiently and reli- ably while acting under uncertainty. One way to achieve efficiency is to give the robot common- sense knowledge about the structure of the world. Reliable robot behaviour can be achieved by mod- elling the uncertainty in the world probabilistically. We present a robot system that combines these two approaches and demonstrate the improvements in efficiency and reliability that result. Our first con- tribution is a probabilistic relational model integrat- ing common-sense knowledge about the world in general, with observations of a particular environ- ment. Our second contribution is a continual plan- ning system which is able to plan in the large prob- lems posed by that model, by automatically switch- ing between decision-theoretic and classical proce- dures. We evaluate our system on object search tasks in two different real-world indoor environ- ments. By reasoning about the trade-offs between possible courses of action with different informa- tional effects, and exploiting the cues and general structures of those environments, our robot is able to consistently demonstrate efficient and reliable goal-directed behaviour

Reconstituting regulation of the canonical Wnt pathway by engineering a minimal β-catenin destruction machine

Negatively regulating key signaling pathways is critical to development and altered in cancer. Wnt signaling is kept off by the destruction complex, which is assembled around the tumor suppressors APC and Axin and targets β-catenin for destruction. Axin and APC are large proteins with many domains and motifs that bind other partners. We hypothesized that if we identified the essential regions required for APC:Axin cooperative function and used these data to design a minimal β-catenin-destruction machine, we would gain new insights into the core mechanisms of destruction complex function. We identified five key domains/motifs in APC or Axin that are essential for their function in reconstituting Wnt regulation. Strikingly, however, certain APC and Axin mutants that are nonfunctional on their own can complement one another in reducing β-catenin, revealing that the APC:Axin complex is a highly robust machine. We used these insights to design a minimal β-catenin-destruction machine, revealing that a minimized chimeric protein covalently linking the five essential regions of APC and Axin reconstitutes destruction complex internal structure, size, and dynamics, restoring efficient β-catenin destruction in colorectal tumor cells. On the basis of our data, we propose a new model of the mechanistic function of the destruction complex as an integrated machine