Nano Science and Technology Institute
Nanotech 2002 Vol. 2
Nanotech 2002 Vol. 2
Technical Proceedings of the 2002 International Conference on Computational Nanoscience and Nanotechnology
 
Chapter 16: Materials and Nanostructures Studies
 

On the Best Performance of Interacting Agents

Authors:V. Korotkich
Affilation:Central Queensland University, AU
Pages:403 - 404
Keywords:interacting agents, energy landscape, complexity, optimality condition
Abstract:Nanotechnology is dependent on harnessing effects of emergent systems, as it relies on the process of taking collections of molecules or individual atoms as building blocks and forming them into useful objects. Emergence can often be viewed when separate systems combine and form a composite system where they act harmoniously together. Most emergent systems can be modelled in terms of the interaction of agents [1]. The potential of using the mechanism involved in emergent systems is enormous as it makes possible activities and controls that are highly unlikely otherwise. But there is still no general framework within which emergent phenomena can be understood (for example [1]). In the paper we consider the following question. Is it possible to have an optimality condition specifying when interacting agents show their best performance for a particular problem. Results of extensive computational experiments presented in the paper give strong facts to believe that such a condition exists and can be formulated in terms of a concept of structural complexity [2]. In the experiments the structural complexity of agents is increased to see how their performance changes. A remarkable result always appears for each problem tested, i.e., performance of the agents unimodally peaks at some point as their structural complexity increases. In general, the experiments allow us to formulate an optimality condition: agents show their best performance for a particular problem when their structural complexity equals the structural complexity of the problem.
On the Best Performance of Interacting AgentsView PDF of paper
ISBN:0-9708275-6-3
Pages:504
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