Decision Maker using Coupled Incompressible-Fluid Cylinders

02/13/2015
by   Song-Ju Kim, et al.
0

The multi-armed bandit problem (MBP) is the problem of finding, as accurately and quickly as possible, the most profitable option from a set of options that gives stochastic rewards by referring to past experiences. Inspired by fluctuated movements of a rigid body in a tug-of-war game, we formulated a unique search algorithm that we call the `tug-of-war (TOW) dynamics' for solving the MBP efficiently. The cognitive medium access, which refers to multi-user channel allocations in cognitive radio, can be interpreted as the competitive multi-armed bandit problem (CMBP); the problem is to determine the optimal strategy for allocating channels to users which yields maximum total rewards gained by all users. Here we show that it is possible to construct a physical device for solving the CMBP, which we call the `TOW Bombe', by exploiting the TOW dynamics existed in coupled incompressible-fluid cylinders. This analog computing device achieves the `socially-maximum' resource allocation that maximizes the total rewards in cognitive medium access without paying a huge computational cost that grows exponentially as a function of the problem size.

READ FULL TEXT
research
04/14/2015

Harnessing Natural Fluctuations: Analogue Computer for Efficient Socially Maximal Decision Making

Each individual handles many tasks of finding the most profitable option...
research
10/30/2014

Efficient Decision-Making by Volume-Conserving Physical Object

We demonstrate that any physical object, as long as its volume is conser...
research
07/02/2018

Multi-User Multi-Armed Bandits for Uncoordinated Spectrum Access

A stochastic multi-user multi-armed bandit framework is used to develop ...
research
10/07/2019

An Option and Agent Selection Policy with Logarithmic Regret for Multi Agent Multi Armed Bandit Problems on Random Graphs

Existing studies of the Multi Agent Multi Armed Bandit (MAMAB) problem, ...
research
01/12/2021

Dynamic Spectrum Access using Stochastic Multi-User Bandits

A stochastic multi-user multi-armed bandit framework is used to develop ...
research
04/07/2012

UCB Algorithm for Exponential Distributions

We introduce in this paper a new algorithm for Multi-Armed Bandit (MAB) ...
research
08/08/2023

AdaptEx: A Self-Service Contextual Bandit Platform

This paper presents AdaptEx, a self-service contextual bandit platform w...

Please sign up or login with your details

Forgot password? Click here to reset