Transcript poster in ppt

ART
Artificial Reasoning Toolkit
Marco Lamieri | Gianluigi Ferraris | University of Turin
The standard algorithm
Some improvement to the method
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The ART (Artificial Reasoning Toolkit) is a pure Java library devoted
to handle Genetic Algorithms and Classifier Systems.
It has been engineered in order to be used into Swarm or others
agent based simulation's models, to easy obtain "minded" agents
who are fully autonomous, able to decide their own behaviors and
able to change it to fit in different environmental conditions.
Another main usage of the algorithm is to search bounded optimal
solutions in very wide solution spaces and for quite undefined
problems. This kind of problems are solved using the convergence
method: the best result is assumed to be achieved when a given
convergence of the same solution exist in the population. It is
widely accepted as mathematical proof that the genetic algorithm,
due to its fitness-proportionate reproduction, converges to better
solutions.
Extended alphabet
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ABSTRACT
THE GENETIC ALGORITHM
Evaluate fitness
f(x)
The genetic algorithm's implementation, starting from
Holland's work, introduces some extensions and innovations:
Multi genome chromosome
Genome 1
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Genome 2
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Genome n
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extended alphabet: each gene can be represented by up to
32000 values. In a standard representation the genes have a
binary alphabet and so the genomes have to be explicitly
translated into the various aspects composing the solution,
which after some manipulation, as crossover or mutation, can
become meaningless. With the extended alphabet each allele
can be a meaningful part of the solution and the translation
process is easier.
multi genome: each individual of the population is
represented by a chromosome that could be composed by a
variable number of genomes. Each genome of a chromosome
represent a "substrategy" and the chromosome is the genetic
algorithm's formalism for a "strategy" driving the actions of the
simulated agent. The multi genome schema give a high degree
of freedom to the user in formalizing problems in which coexist
different binded aspects.
Rescale fitness
rescale fitness operator: the natural selection process has
been modified in order to improve efficiency and manage
negative fitness values. The technique utilized consist in rescale
the fitness of all the chromosome.
Population
Fitness
Rescale fitness
univocal genome: using this option each value of the alphabet
is unique whitin the genome, it means that in a genome there
can not be two or more identical genes.
FUTURE AIMS
1. Develop a Classifier System.
2. Construct cluster and ring of genetic algorithms.
3. Run the library on high performance computers (cluster and grid).
Univocal genome
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References
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1) ART project homepage: http://eco83.econ.unito.it/golem
2) Darwin, C., The Origin of Species, Viking Press, 1982.
3) Holland, J. H., Adaptation in Natural and Artificial Systems, MIT Press, 1992.