Efficient Decision-Making by Volume-Conserving Physical Object
  We demonstrate that any physical object, as long as its volume is conserved when coupled with suitable operations, provides a sophisticated decision-making capability. We consider the problem of finding, as accurately and quickly as possible, the most profitable option from a set of options that gives stochastic rewards. These decisions are made as dictated by a physical object, which is moved in a manner similar to the fluctuations of a rigid body in a tug-of-war game. Our analytical calculations validate statistical reasons why our method exhibits higher efficiency than conventional algorithms. 
Song-Ju Kim, Masashi Aono, and Etsushi Nameda
cs.AI cs.LG nlin.AO physics.data-an