@InProceedings{heywood:2000:rbGPFPGA,
author = "M. I. Heywood and A. N. Zincir-Heywood",
title = "Register Based Genetic Programming on {FPGA} Computing
Platforms",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "44--59",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "The use of FPGA based custom computing platforms is
proposed for implementing linearly structured Genetic
Programs. Such a context enables consideration of micro
architectural and instruction design issues not
normally possible when using classical Von Neumann
machines. More importantly, the desirability of
minimising memory management overheads results in the
imposition of additional constraints to the crossover
operator. Specifically, individuals are described in
terms of the number of pages and page length, where the
page length is common across individuals of the
population. Pairwise crossover therefore results in the
swapping of equal length pages, hence minimising memory
overheads. Simulation of the approach demonstrates that
the method warrants further study.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{martin:2000:GPscin,
author = "Peter Martin",
title = "Genetic Programming for Service Creation in
Intelligent Networks",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "106--120",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "Intelligent Networks are used by telephony systems to
offer services to customers. The creation of these
services has traditionally been performed by hand, and
has required substantial effort, despite the advanced
tools employed. An alternative to manual service
creation using Genetic Programming is proposed that
addresses some of the limitations of the manual process
of service creation. The main benefit of using GP is
that by focussing on what a service is required to do,
as opposed to its implementation, it is more likely
that the generated programs will be available on time
and to budget, when compared to traditional software
engineering techniques. The problem of closure is
tackled by presenting a new technique for ensuring
correct program syntax that maintains genetic
diversity.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{poli:2000:GP,
title = "Genetic Programming, Proceedings of Euro{GP}'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
size = "361 pages",
notes = "EuroGP'2000",
}
@InProceedings{poli:2000:htGP1xbb,
author = "R. Poli",
title = "Hyperschema Theory for {GP} with One-Point Crossover,
Building Blocks, and Some New Results in {GA} Theory",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "163--180",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "Two main weaknesses of GA and GP schema theorems are
that they provide only information on the expected
value of the number of instances of a given schema at
the next generation E[m(H,t+1)], and they can
only give a lower bound for such a quantity. This paper
presents new theoretical results on GP and GA schemata
which largely overcome these weaknesses. Firstly,
unlike previous results which concentrated on schema
survival and disruption, our results extend to GP
recent work on GA theory by Stephens and Waelbroeck,
and make the effects and the mechanisms of schema
creation explicit. This allows us to give an exact
formulation (rather than a lower bound) for the
expected number of instances of a schema at the next
generation. Thanks to this formulation we are then able
to provide in improved version for an earlier GP schema
theorem in which some schema creation events are
accounted for, thus obtaining a tighter bound for
E[m(H,t+1)]. This bound is a function of the
selection probabilities of the schema itself and of a
set of lower-order schemata which one-point crossover
uses to build instances of the schema. This result
supports the existence of building blocks in GP which,
however, are not necessarily all short, low-order or
highly fit. Building on earlier work, we show how
Stephens and Waelbroeck's GA results and the new GP
results described in the paper can be used to evaluate
schema variance, signal-to-noise ratio and, in general,
the probability distribution of m(H,t+1). In
addition, we show how the expectation operator can be
removed from the schema theorem so as to predict with a
known probability whether m(H,t+1) (rather than
E[m(H,t+1)]) is going to be above a given
threshold.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{muruzabal:2000:pmbcGP,
author = "Jorge Muruzabal and Carlos Cotta-Porras and Amelia
Fernandez",
title = "Some Probabilistic Modelling Ideas For Boolean
Classification In Genetic Programming",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "133--148",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "We discuss the problem of boolean classification via
Genetic Programming. When predictors are numeric, the
standard approach proceeds by classifying according to
the sign of the value provided by the evaluated
function. We consider an alternative approach whereby
the magnitude of such a quantity also plays a role in
prediction and evaluation. Specifically, the original,
unconstrained value is transformed into a probability
value which is then used to elicit the classification.
This idea stems from the well-known logistic regression
paradigm and can be seen as an attempt to squeeze all
the information in each individual function. We
investigate the empirical behaviour of these variants
and discuss a third evaluation measure equally based on
probabilistic ideas. To put these ideas in perspective,
we present comparative results obtained by alternative
methods, namely recursive splitting and logistic
regression.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{koza:2000:ecfvGP,
author = "John R. Koza and Martin A. Keane and Jessen Yu and
Forrest H {Bennett III} and William Mydlowec",
title = "Evolution of a Controller with a Free Variable using
Genetic Programming",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "91--105",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "A mathematical formula containing one or more free
variables is {"}general{"} in the sense that it
provides a solution to an entire category of problems.
For example, the familiar formula for solving a
quadratic equation contains free variables representing
the equation's coefficients. Previous work has
demonstrated that genetic programming can automatically
synthesize the design for a controller consisting of a
topological arrangement of signal processing blocks
(such as integrators, differentiators, leads, lags,
gains, adders, inverters, and multipliers), where each
block is further specified ({"}tuned{"}) by a numerical
component value, and where the evolved controller
satisfies user-specified requirements. The question
arises as to whether it is possible to use genetic
programming to automatically create a {"}generalized{"}
controller for an entire category of such controller
design problems instead of a single instance of the
problem. This paper shows, for an illustrative problem,
how genetic programming can be used to create the
design for both the topology and tuning of controller,
where the controller contains a free variable.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{drost:2000:mbea,
author = "Stefan Droste and Dirk Wiesmann",
title = "Metric Based Evolutionary Algorithms",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "29--43",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "In this article a set of guidelines for the design of
genetic operators and the representation of the
phenotype space is proposed. These guidelines should
help to systematize the design of problem-specific
evolutionary algorithms. Hence, they should be
particularly beneficial for the design of genetic
programming systems. The applicability of this concept
is shown by the systematic design of a genetic
programming system for finding Boolean functions. This
system is the first GP-system, that reportedly found
the 12 parity function.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{vanyi:2000:grden,
author = "Robert Vanyi and Gabriella Kokai and Zoltan Toth and
T-unde Peto",
title = "Grammatical Retina Description with Enhanced Methods",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "193--208",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "In this paper the enhanced version of the GREDEA
system is presented. The main idea behind the system is
that with the help of evolutionary algorithms a
grammatical description of the blood circulation of the
human retina can be inferred. The system uses
parametric Lindenmayer systems as description language.
It can be applied on patients with diabetes who need to
be monitored over long periods of time. Since the first
version some improvements were made, e.g. new fitness
function and new genetic operators. In this paper these
changes are described.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{albuquerque:2000:irfl,
author = "Paul Albuquerque and Bastien Chopard and Christian
Mazza and Marco Tomassini",
title = "On the Impact of the Representation on Fitness
Landscapes",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "1--15",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "In this paper we study the role of program
representation on the properties of a type of Genetic
Programming (GP) algorithm. In a specific case, which
we believe to be generic of standard GP, we show that
the way individuals are coded is an essential concept
which impacts the fitness landscape. We give evidence
that the ruggedness of the landscape affects the
behavior of the algorithm and we find that, below a
critical population, whose size is
representation-dependent, premature convergence
occurs.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{oneill:2000:xGEso,
author = "Michael O'Neill and Conor Ryan",
title = "Crossover in Grammatical Evolution: {A} Smooth
Operator?",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "149--162",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "Grammatical Evolution is an evolutionary algorithm
which can produce code in any language, requiring as
inputs a BNF grammar definition describing the output
language, and the fitness function. The usefulness of
crossover in GP systems has been hotly debated for some
time, and this debate has also arisen with respect to
Grammatical Evolution. This paper serves to analyse the
crossover operator in our algorithm by comparing the
performance of a variety of crossover operators.
Results show that the standard one point crossover
employed by Grammatical Evolution is not as destructive
as it might originally appear, and is useful in
performing a global search over the course of entire
runs. This is attributed to the fact that prior to the
crossover event the parent chromosomes undergo
alignment which facilitates the swapping of blocks
which are more likely to be in context.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{bongard:2000:legion,
author = "Josh C. Bongard",
title = "The Legion System: {A} Novel Approach to Evolving
Heterogeneity for Collective Problem Solving",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "16--28",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "We investigate the dynamics of agent groups evolved to
peform a collective task, and in which the behavioural
heterogeneity of the group is under evolutionary
control. Two task domains are studied: solutions are
evolved for the two tasks using an evolutionary
algorithm called the Legion system. A new metric of
heterogeneity is also introduced, which measures the
heterogeneity of evolved group behaviours. It was found
that the amount of heterogeneity evolved in an agent
group is dependent on the given problem domain: for the
first task, the Legion system evolved heterogeneous
groups; for the second task, primarily homogeneous
groups evolved. We conclude that the proposed system,
in conjunction with the introduced heterogeneity
measure, can be used as a tool for investigating
various issues concerning redundancy, robustness and
division of labour in the context of evolutionary
approaches to collective problem solving.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{rodriguez-vazquez:2000:GPirms,
author = "Katya Rodriguez-Vazquez and Peter J. Fleming",
title = "Use of Genetic Programming In The Identification Of
Rational Model Structures",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "181--192",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "This paper demonstrates how genetic programming can be
used for solving problems in the field of non-linear
system identification of rational models. By using a
two-tree structure rather than introducing the division
operator in the function set, this genetic programming
approach is able to determine the `true' model
structure of the system under investigation. However,
unlike use of the polynomial, which is linear in the
parameters, use of rational model is non-linear in the
parameters and thus noise terms cannot be estimated
properly. By means of a second optimisation process
(real-coded GA) which has the aim of tunning the
coefficients to the `true' values, these parameters are
then correctly computed. This approach is based upon
the well-known NARMAX model representation, widely used
in non-linear system identification.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{alganova:2000:efemvlf,
author = "Tatiana Kalganova",
title = "An Extrinsic Function-Level Evolvable Hardware
Approach",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "60--75",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "The function level evolvable hardware approach to
synthesize the combinational multi-valued and binary
logic functions is proposed in first time. The new
representation of logic gate in extrinsic EHW allows us
to describe behaviour of any multi-input multi-output
logic function. The circuit is represented in the form
of connections and functionalities of a rectangular
array of building blocks. Each building block can
implement primitive logic function or any multi-input
multi-output logic function defined in advance. The
method has been tested on evolving logic circuits using
half adder, full adder and multiplier. The
effectiveness of this approach is investigated for
multi-valued and binary arithmetical functions. For
these functions either method appears to be much more
efficient than similar approach with two-input
one-output cell representation.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{keijzer:2000:GPbvt,
author = "Maarten Keijzer and Vladan Babovic",
title = "Genetic Programming, Ensemble Methods and the
Bias/Variance Tradeoff - Introductory Investigations",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "76--90",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{miller:2000:CGP,
author = "Julian F. Miller and Peter Thomson",
title = "Cartesian Genetic Programming",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "121--132",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "This paper presents a new form of Genetic Programming
called Cartesian Genetic Programming in which a program
is represented as an indexed graph. The graph is
encoded in the form of a linear string of integers. The
inputs or terminal set and node outputs are numbered
sequentially. The node functions are also separately
numbered. The genotype is just a list of node
connections and functions. The genotype is then mapped
to an indexed graph that can be executed as a program.
Evolutionary algorithms are used to evolve the genotype
in a symbolic regression problem (sixth order
polynomial) and the Santa Fe Ant Trail. The
computational effort is calculated for both cases. It
is suggested that hit effort is a more reliable measure
of computational efficiency. A neutral search strategy
that allows the fittest genotype to be replaced by
another equally fit genotype (a neutral genotype) is
examined and compared with non-neutral search for the
Santa Fe ant problem. The neutral search proves to be
much more effective.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{ryan:2000:paragen1,
author = "Conor Ryan and Laur Ivan",
title = "Paragen - The first results",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "338--348",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{ekart:2000:mGPfs,
author = "Aniko Ekart and S. Z. Nemeth",
title = "A metric for genetic programs and fitness sharing",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "259--270",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "In the paper a metric for genetic programs is
constructed. This metric reflects the structural
difference of the genetic programs. It is used then for
applying fitness sharing to genetic programs, in
analogy with fitness sharing applied to genetic
algorithms. The experimental results for several
parameter settings are discussed. We observe that by
applying fitness sharing the code growth of genetic
programs could be limited.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{langdon:2000:seed,
author = "W. B. Langdon and J. P. Nordin",
title = "Seeding {GP} Populations",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "304--315",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
email = "W.B.Langdon@cwi.nl nordin@fy.chalmers.se",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "We show GP populations can evolve from ``perfect''
programs which match the training material under the
influence of a Pareto multi-objective fitness and
program size selection scheme to generalise. The
technique is demonstrated upon programmatic image
compression, two machine learning benchmark problems
(Pima Diabetes and Wisconsin Breast Cancer) and a
consumer profiling task (Benelearn99).",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{podgorelec:2000:fpbfcm,
author = "Vili Podgorelec and Kokol",
title = "Fighting Program Bloat with the Fractal Complexity
Measure",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "326--337",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "The problem of evolving decision programs to be used
for medical diagnosis prediction brought us to the
problem, well know to the genetic programming (GP)
community: the tendency of programs to grow in length
too fast. While searching for a solution we found out
that an appropriately defined fractal complexity
measure can differentiate between random and non-random
computer programs by measuring the fractal structure of
the computer programs. Knowing this fact, we introduced
the fractal measure alpha in the evaluation and
selection phase of the evolutionary process of decision
program induction, which resulted in a significant
program bloat reduction.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{bot:2000:GPilct,
author = "Martijn C. J. Bot and William B. Langdon",
title = "Application of Genetic Programming to Induction of
Linear Classification Trees",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "247--258",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "A common problem in datamining is to find accurate
classifiers for a dataset. For this purpose, genetic
programming (GP) is applied to a set of benchmark
classification problems. Using GP we are able to induce
decision trees with a linear combination of variables
in each function node. A new representation of decision
trees using strong typing in GP is introduced. With
this representation it is possible to let the GP
classify into any number o f classes. Results indicate
that GP can be applied successfully to classification
problems. Comparisons with current state-of-the-art
algorithms in machine learning are presented and areas
of future research are identified.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{bergstrom:2000:atrawGP,
author = "Agneta Bergstrom and Patricija Jaksetic and Peter
Nordin",
title = "Acquiring Textual Relations Automatically on the Web
using Genetic Programming",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "237--246",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{feldt:2000:feeeGP,
author = "Robert Feldt and Peter Nordin",
title = "Using Factorial Experiments to Evaluate the Effect of
Genetic Programming Parameters",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "271--282",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "Statistical techniques for designing and analyzing
experiments are used to evaluate the individual and
combined effects of genetic programming parameters.
Three binary classification problems are investigated
in a total of seven experiments consisting of 1108 runs
of a machine code genetic programming system. The
parameters having the largest effect in these
experiments are the population size and the number of
generations. A large number of parameters have
negligible effects. The experiments indicate that the
investigated genetic programming system is robust to
parameter variations, with the exception of a few
important parameters.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{folino:2000:GPSAhmeDT,
author = "Gianluigi Folino and Clara Pizzuti and Giandomenico
Spezzano",
title = "Genetic Programming and Simulated Annealing: {A}
Hybrid Method to Evolve Decision Trees",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "294--303",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "A method for the data mining task of data
classification, suitable to be implemented on massively
parallel architectures, is proposed. The method
combines genetic programming and simulated annealing to
evolve a population of decision trees. A cellular
automaton is used to realise a fine-grained parallel
implementation of genetic programming through the
diffusion model and the annealing schedule to decide
the acceptance of a new solution. Preliminary
experimental results, obtained by simulating the
behaviour of the cellular automaton on a sequential
machine, show significant better performances with
respect to C4.5.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{baglioni:2000:eampaa,
author = "Stefania Baglioni and Celia da Costa Pereira and Dario
Sorbello and Andrea G. B. Tettamanzi",
title = "An Evolutionary Approach to Multiperiod Asset
Allocation",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "225--236",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "Portfolio construction can become a very complicated
problem, as regulatory constraints, individual
investor's requirements, non-trivial indices of risk
and subjective quality measures are taken into account,
together with multiple investment horizons and
cash-flow planning. This problem is approached using a
tree of possible scenarios for the future, and an
evolutionary algorithm is used to optimize an
investment plan against the desired criteria and the
possible scenarios. An application to a real defined
benefit pension fund case is discussed.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{zhao:2000:mrccGP,
author = "Kai Zhao and Jue Wang",
title = "Multi-robot cooperation and competition with genetic
programming",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "349--360",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "In this paper, we apply Genetic Programming (GP) on
multi-robot cooperation and competition problem. GP is
taken as a real time planning method in stead of
learning method. Robot all use GP to make a plan and
then walk according to the plan. The environment is
composed of two parts, natural environment, which is
the obstacles, and social environment that refers to
other robots. The cooperation process is accomplished
by robot's adaptation to both of them. In spite of the
fact that there is no communication among robots and
little knowledge about how to cooperate well, the
adaptive capability in dynamic environment enable
robots to complete a common task or solve the
competition. Several experiments are taken and the
results are shown.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{akira:2000:moelGP,
author = "Yoshida Akira",
title = "Intraspecific Evolution of Learning by Genetic
Programming",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "209--224",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{lukschandl:2000:DJBGP,
author = "Eduard Lukschandl and Henrik Borgvall and Lars Nohle
and Mats Nordahl and Peter Nordin",
title = "Distributed Java Bytecode Genetic Programming",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "316--325",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "This paper describes a method for evolutionary program
induction of binary Java bytecode. Like many other
machine code based methods it uses a linear genome. The
genetic operators are adapted to the stack architecture
and preserve stack depth during crossover. In this work
we have extended a previous system to run in a
distributed manner on several different physical
machines. We call our new system Distributed Java
Bytecode Genetic Programming (DJBGP). We use the
Voyager package for migration of Java individuals. The
system's feasibility is demonstrated on a telecom
routing problem.",
notes = "EuroGP'2000, part of poli:2000:GP",
}
@InProceedings{fernandez:2000:esmpGP,
author = "F. Fernandez and M. Tomassini and W. F. {Punch III}
and J. M. Sanchez",
title = "Experimental Study of Multipopulation Parallel Genetic
Programming",
booktitle = "Genetic Programming, Proceedings of EuroGP'2000",
year = "2000",
editor = "Riccardo Poli and Wolfgang Banzhaf and William B.
Langdon and Julian F. Miller and Peter Nordin and
Terence C. Fogarty",
volume = "1802",
series = "LNCS",
pages = "283--293",
address = "Edinburgh",
publisher_address = "Berlin",
month = "15-16 " # apr,
organisation = "EvoNet",
publisher = "Springer-Verlag",
keywords = "genetic algorithms, genetic programming",
ISBN = "3-540-67339-3",
abstract = "The parallel execution of several populations in
evolutionary algorithms has usually given good results.
Nevertheless, researchers have to date drawn
conflicting conclusions when using some of the parallel
genetic programming models. One aspect of the conflict
is population size, since published GP works do not
agree about whether to use large or small populations.
This paper presents an experimental study of a number
of common GP test problems. Via our experiments, we
discovered that an optimal range of values exists. This
assists us in our choice of population size and in the
selection of an appropriate parallel genetic
programming model. Finding efficient parameters helps
us to speed up our search for solutions. At the same
time, it allows us to locate features that are common
to parallel genetic programming and the classic genetic
programming technique.",
notes = "EuroGP'2000, part of poli:2000:GP",
}