Csáji, Balázs Csanád and Monostori, László (2006) Adaptive algorithms in distributed resource allocation. In: IWES 2006. 6th international workshop on emergent synthesis. Tokyo, 2006..

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Abstract

The allocation of scarce, reusable resources over time to interconnected tasks in uncertain and dynamic envi- ronments in order to optimize a performance measure is a general problem which arises in many real-world domains. The paper overviews several recent distrib- uted approaches to this problem and compares their properties, such as the guarantees of ¯nding a (near-) optimal solution, their robustness against di®erent dis- turbances or against imprecise, uncertain models, with a special emphasis on their adaptive capabilities. The paper argues that reinforcement learning based distrib- uted resource allocation systems represent one of the most promising approaches to these kinds of problems.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	resource allocation, distributed optimization, stochastic processes, reinforcement learning
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions:	Research Laboratory on Engineering & Management Intelligence
Depositing User:	Eszter Nagy
Date Deposited:	11 Dec 2012 15:26
Last Modified:	24 Jul 2018 10:40
URI:	https://eprints.sztaki.hu/id/eprint/4458

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