Artificial Life Approach for Continuous Optimisation of Non Stationary Dynamical Systems
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- @Article{AnnunziatoL2003:ICAE,
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author = "Mauro Annunziato and Carlo Bruni and
Matteo Lucchetti and Stefano Pizzuti",
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title = "Artificial Life Approach for Continuous Optimisation
of Non Stationary Dynamical Systems",
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journal = "Integrated Computer-Aided Engineering",
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year = "2003",
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volume = "10",
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number = "2",
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pages = "111--125",
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email = "lucchetti@dis.uniroma1.it",
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keywords = "genetic algorithms, genetic programming, artificial
life",
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ISSN = "1069-2509",
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URL = "http://content.iospress.com/articles/integrated-computer-aided-engineering/ica00140",
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DOI = "doi:10.3233/ICA-2003-10202",
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size = "15 pages",
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abstract = "In this paper, we develop an intelligent system to
approach dynamical optimisation problems emerging in
control of complex systems. In particular our proposal
is to exploit the adaptivity of an artificial life
(alife) environment in order to achieve 'not control
rules but autonomous structures able to dynamically
adapt and to generate optimised-control rules'. The
basic features of the proposed approach are: no
intensive modelling (continuous learning directly from
measurements) and capability to follow the system
evolution (adaptation to environmental changes). The
suggested methodology has been tested on an energy
regulation problem deriving from a classical testbed in
dynamical systems experimentations: the Chua's circuit.
We supposed not to know the system dynamics and to be
able to act only on a subset of control parameters,
letting the others vary in time in a random discrete
way. We let the optimisation process searching for the
new best value of performance, whenever a drop due to
changes in fitness landscape occurred. We present the
most important results showing the effectiveness of the
proposed approach in adapting to environmental
non-stationary changes by recovering the optimal value
of process performance.",
- }
Genetic Programming entries for
Mauro Annunziato
Carlo Bruni
Matteo Lucchetti
Stefano Pizzuti
Citations