AIFeb 13, 2015

Decision Maker using Coupled Incompressible-Fluid Cylinders

arXiv:1502.03890v12 citations
Originality Incremental advance
AI Analysis

This addresses channel allocation in cognitive radio for improved efficiency, but it is incremental as it builds on existing tug-of-war dynamics.

The paper tackles the competitive multi-armed bandit problem in cognitive radio by proposing a physical device called the 'TOW Bombe' based on coupled incompressible-fluid cylinders, which achieves socially-maximum resource allocation without exponential computational cost growth.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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