Collectives for the Optimal Combination of Imperfect Objects

TL;DR

This paper discusses the design of agent collectives to optimize the combination of imperfect nano-scale objects, demonstrating algorithms that significantly outperform conventional methods in this task.

Contribution

It introduces new algorithms based on recent theoretical work for optimizing systems of agents, applied to nano-object combination problems.

Findings

Algorithms outperform conventional methods by over tenfold

Effective in optimizing imperfect nano-scale object combinations

Applicable to systems with many agents and complex utilities

Abstract

In this letter we summarize some recent theoretical work on the design of collectives, i.e., of systems containing many agents, each of which can be viewed as trying to maximize an associated private utility, where there is also a world utility rating the behavior of that overall system that the designer of the collective wishes to optimize. We then apply algorithms based on that work on a recently suggested testbed for such optimization problems (Challet & Johnson, PRL, vol 89, 028701 2002). This is the problem of finding the combination of imperfect nano-scale objects that results in the best aggregate object. We present experimental results showing that these algorithms outperform conventional methods by more than an order of magnitude in this domain.