Efficient Decision-Making by Volume-Conserving Physical Object
This presents a novel approach to decision-making problems, potentially impacting optimization and AI applications.
The paper tackles the problem of efficiently selecting the most profitable option from stochastic rewards by using a volume-conserving physical object to guide decision-making, demonstrating higher efficiency than conventional algorithms through analytical validation.
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.