Harnessing the Computational Power of Fluids for Optimization of Collective Decision Making

Abstract

How can we harness nature's power for computations? Our society comprises a collection of individuals, each of whom handles decision-making tasks that are abstracted as computational problems of finding the most profitable option from a set of options that stochastically provide rewards. Society is expected to maximize the total rewards, while the individuals compete for common rewards. Such collective decision making is formulated as the "competitive multi-armed bandit problem (CBP)." Herein, we demonstrate an analog computing device that uses numerous fluids in coupled cylinders to efficiently solve CBP for the maximization of social rewards, without paying the conventionally-required huge computational cost. The fluids estimate the reward probabilities of the options for the exploitation of past knowledge, and generate random fluctuations for the exploration of new knowledge for which the utilization of the fluid-derived fluctuations is more advantageous than applying artificial fluctuations. The fluid-derived fluctuations, which require exponentially-many combinatorial efforts when they are emulated using conventional digital computers, would exhibit their maximal computational power when tackling classes of problems that are more complex than CBP. Extending the current configuration of the device would trigger further studies related to harnessing the huge computational power of natural phenomena to solve a wide variety of complex societal problems.

Entangled-photon decision maker

“…This type of decision-making problem becomes even more difficult when the number of decision makers, i.e. the number of individuals who join the game or simultaneously play the slot machines, is multiple; then the problem is referred to as a competitive multi-armed bandit (CMAB) problem 12,13 , which is the focus of the study described herein. In collective decision making, social values are highlighted, such as the maximization of the total social benefits, guarantee of equality among individuals, and so on [12][13][14][15] .…”

“…the number of individuals who join the game or simultaneously play the slot machines, is multiple; then the problem is referred to as a competitive multi-armed bandit (CMAB) problem 12,13 , which is the focus of the study described herein. In collective decision making, social values are highlighted, such as the maximization of the total social benefits, guarantee of equality among individuals, and so on [12][13][14][15] . The CMAB problem is important in practical applications ranging from traffic control, where everyone choosing the same road may lead to a traffic jam 16 to resource allocation in infrastructures, such as communications 12,17 where everyone wanting to communicate at the same time leads to congestion for example.…”

Ionic decision-maker created as novel, solid-state devices

“…The ionic decision-maker developed in the present study is efficiently used for this decision-making. For this purpose, we use the TOW principle that resembles the TOW game in which two persons, A and B, pull against each other at opposite ends of a rigid rope ( 7 , 14 , 25 ). Physically, the TOW principle consists of two key points, that is, the conservation of some physical quantity (which corresponds to the length of the abovementioned rigid rope) and a certain stochastic fluctuation (corresponding to the fluctuation of the horizontal position of the rigid rope, which will be discussed in detail later) ( 2 , 7 , 14 ).…”

“…Our ionic decision-maker demonstrates the ability to solve competitive MBPs, which suffer serious loss of rewards (for example, throughput in communication networks) due to the Nash equilibrium (NE), which is the natural consequence for a group of independent selfish users ( 7 , 30 , 31 ). Excellent throughput has been demonstrated by overall optimization of the selections made by users in a communication network.…”

Computing with Nature

“…Advanced forms of such research have for instance objectives of the development of molecular or cellular robotics [6,7]. The other direction is to search for processes in nature which can provide examples of unconventional forms of computation, for instance reversible computation [8][9][10]. The directions are opposite in the sense that one assumes already existing conventional model of computation and looks up for their implementation in nature, the other explores nature in the search for new forms of computation.…”