Efficient Decision-Making by Volume-Conserving Physical Object
Artificial Intelligence
2015-09-02 v1 Machine Learning
Adaptation and Self-Organizing Systems
Data Analysis, Statistics and Probability
Abstract
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.
Cite
@article{arxiv.1412.6141,
title = {Efficient Decision-Making by Volume-Conserving Physical Object},
author = {Song-Ju Kim and Masashi Aono and Etsushi Nameda},
journal= {arXiv preprint arXiv:1412.6141},
year = {2015}
}
Comments
5 pages, 3 figures