From: Candida Ferreira (candidaf@gene-expression-programming.com)
Date: Tue Nov 14 2000 - 15:05:07 MST
~Hi all,
My paper on gene expression programming is now available as a pdf for download at my site:
http://www.gene-expression-programming.com
Be advised that different versions of this paper were submitted and rejected by ^ÓNature^Ô and ^ÓGenetic Programming and Evolvable Machines^Ô. One of the reasons one anonymous reviewer from GPEM gave was that ^ÓThe performance of the GEP algorithm compared to GP seems too good to be true to me.^Ô
As I really want to see other scientists using GEP in other applications, I decided to publish my paper on the web in order to make this powerful algorithm available to all. Remember, though, that there is a patent pending and GEP can not be used commercially.
Best regards,
Candida Ferreira
TITLE:
Gene Expression Programming: a New Adaptive Algorithm for Solving Problems
AUTHOR:
Candida Ferreira
ABSTRACT:
Gene expression programming, a genome/phenome genetic algorithm (linear and non-linear), is presented here for the first time as a new technique for creation of computer programs. Gene expression programming uses character linear chromosomes composed of genes structurally organised in a head and a tail. The chromosomes function as a genome and are subjected to modification by means of mutation, transposition, root transposition, gene transposition, gene recombination, 1-point and 2-point recombination. The chromosomes encode expression trees which are the object of selection. The creation of these separate entities (genome and expression tree) with distinct functions allows the algorithm to perform with high efficiency: in the symbolic regression, sequence induction and block stacking problems it surpasses genetic programming in more than two orders of magnitude, whereas in the density-classification problem it surpasses genetic programming in more than four orders of magnitude. The suite of problems chosen
to illustrate the power and versatility of gene expression programming includes, besides the above mentioned problems, two problems of Boolean concept learning: the 11-multiplexer and the GP rule problem.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Candida Ferreira, PhD
Assistant Professor of Biochemistry
Department of Agricultural Sciences
The Azores University
Email: candidaf@gene-expression-programming.com
http://www.gene-expression-programming.com
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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GRADUATE TRAINING IN THE
DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS (CNS)
AT BOSTON UNIVERSITY
*******************************************************************
The Boston University Department of Cognitive and Neural Systems
offers comprehensive graduate training in the neural and computational
principles, mechanisms, and architectures that underlie human and
animal behavior, and the application of neural network architectures
to the solution of technological problems.
The brochure may also be viewed on line at:
http://www.cns.bu.edu/brochure/
and application forms at:
Applications for Fall 2001 admission and financial aid are now being
accepted for both the MA and PhD degree programs.
To obtain a brochure describing the CNS Program and a set of application
materials, write, telephone, or fax:
DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS
Boston University
677 Beacon Street
Boston, MA 02215
617/353-9481 (phone)
617/353-7755 (fax)
or send via e-mail your full name and mailing address to the attention
of Mr. Robin Amos at:
Applications for admission and financial aid should be received by the
Graduate School Admissions Office no later than January 15. Late
applications will be considered until May 1; after that date
applications will be considered only as special cases.
Applicants are required to submit undergraduate (and, if applicable,
graduate) transcripts, three letters of recommendation, and Graduate
Record Examination (GRE) scores. The Advanced Test should be in the
candidate's area of departmental specialization. GRE scores may be
waived for MA candidates and, in exceptional cases, for PhD
candidates, but absence of these scores will decrease an applicant's
chances for admission and financial aid.
Non-degree students may also enroll in CNS courses on a part-time
basis.
*******************************************************************
Description of the CNS Department:
The Department of Cognitive and Neural Systems (CNS) provides advanced
training and research experience for graduate students interested in
the neural and computational principles, mechanisms, and
architectures that underlie human and animal behavior, and the
application of neural network architectures to the solution of
outstanding technological problems. Students are trained in a broad
range of areas concerning computational neuroscience, cognitive
science, and neuromorphic systems, including the brain mechanisms of
vision and visual object recognition; audition, speech, and language
understanding; recognition, learning, categorization, and long-term
memory; cognitive information processing; self-organization and
development; navigation, planning, and spatial orientation;
cooperative and competitive network dynamics and short-term memory;
reinforcement and motivation; attention; adaptive sensory-motor
control and robotics; biological rhythms; consciousness; mental
disorders; and the mathematical and computational methods needed to
support advanced modeling research and applications. The CNS
Department awards MA, PhD, and BA/MA degrees.
The CNS Department embodies a number of unique features. It has
developed a curriculum that consists of eighteen interdisciplinary
graduate courses, each of which integrates the psychological,
neurobiological, mathematical, and computational information needed
to theoretically investigate fundamental issues concerning mind and
brain processes and the applications of neural networks to
technology. Additional advanced courses, including research
apprenticeship and seminar courses, are also offered. Each course is
typically taught once a week in the afternoon or evening to make the
program available to qualified students, including working
professionals, throughout the Boston area. Students develop a
coherent area of expertise by designing a program that includes
courses in areas such as biology, computer science, engineering,
mathematics, and psychology, in addition to courses in the CNS
curriculum.
The CNS Department interacts with colleagues in several Boston
University research centers or groups, and with Boston-area
scientists collaborating with these centers. The unit most closely
linked to the department is the Center for Adaptive Systems.
Students interested in neural network hardware can work with
researchers in CNS, at the College of Engineering, and at M.I.T.
Lincoln Laboratory. Other research resources include distinguished
research groups in neurophysiology, neuroanatomy, and neuropharmacology
across the Boston University Charles River Campus and Medical School;
in sensory robotics, biomedical engineering, computer and systems
engineering, and neuromuscular research within the College of
Engineering; in dynamical systems within the Mathematics Department;
in theoretical computer science within the Computer Science
Department; and in biophysics and computational physics within the
Physics Department. Key colleagues in these units hold appointments
in CNS.
In addition to its basic research and training program, the
department conducts a seminar series, as well as conferences and
symposia, which bring together distinguished scientists from both
experimental, theoretical, and applied disciplines.
The department is housed in its own four-story building which
includes ample space for faculty and student offices and laboratories
(computational neuroscience, visual psychophysics, psychoacoustics,
speech and language, sensory-motor control, neurobotics, computer
vision), as well as an auditorium, classroom and seminar rooms, a
library, and a faculty-student lounge. The department has a powerful
computer network for carrying out large-scale simulations of
behavioral and brain models.
Below are listed departmental faculty, courses and labs.
FACULTY AND STAFF OF THE DEPARTMENT OF COGNITIVE AND NEURAL
SYSTEMS AND CENTER FOR ADAPTIVE SYSTEMS
Jelle Atema
Professor of Biology
Director, Boston University Marine Program (BUMP)
PhD, University of Michigan
Sensory physiology and behavior.
Helen Barbas
Professor of Anatomy and Neurobiology, Boston University School of Medicine
PhD, Physiology/Neurophysiology, McGill University
Organization of the prefrontal cortex, evolution of the neocortex.
Jacob Beck
Research Professor of Cognitive and Neural Systems
PhD, Psychology, Cornell University
Visual perception, psychophysics, computational models of vision.
Daniel H. Bullock
Associate Professor of Cognitive and Neural Systems, and Psychology
PhD, Experimental Psychology, Stanford University
Sensory-motor performance and learning, voluntary control of action,
serial order and timing, cognitive development.
Gail A. Carpenter
Professor of Cognitive and Neural Systems and Mathematics
Director of Graduate Studies, Department of Cognitive and Neural Systems
PhD, Mathematics, University of Wisconsin, Madison
Learning and memory, synaptic processes, pattern recognition, remote
sensing,
medical database analysis, machine learning, differential equations.
Michael A. Cohen
Associate Professor of Cognitive and Neural Systems and Computer Science
PhD, Psychology, Harvard University
Speech and language processing, measurement theory, neural modeling,
dynamical systems, cardiovascular oscillations physiology and time series.
H. Steven Colburn
Professor of Biomedical Engineering
PhD, Electrical Engineering, Massachusetts Institute of Technology
Audition, binaural interaction, auditory virtual environments,
signal processing models of hearing.
Howard Eichenbaum
Professor of Psychology
PhD, Psychology, University of Michigan
Neurophysiological studies of how the hippocampal system mediates
declarative memory.
William D. Eldred III
Professor of Biology
PhD, University of Colorado, Health Science Center
Visual neuralbiology.
Paolo Gaudiano
Research Associate Professor of Cognitive and Neural Systems
PhD, Cognitive and Neural Systems, Boston University
Computational and neural models of robotics, vision, adaptive sensory-motor
control, and behavioral neurobiology.
Jean Berko Gleason
Professor of Psychology
PhD, Harvard University
Psycholinguistics.
Sucharita Gopal
Associate Professor of Geography
PhD, University of California at Santa Barbara
Neural networks, computational modeling of behavior, geographical
information
systems, fuzzy sets, and spatial cognition.
Stephen Grossberg
Wang Professor of Cognitive and Neural Systems
Professor of Mathematics, Psychology, and Biomedical Engineering
Chairman, Department of Cognitive and Neural Systems
Director, Center for Adaptive Systems
PhD, Mathematics, Rockefeller University
Vision, audition, language, learning and memory, reward and motivation,
cognition, development, sensory-motor control, mental disorders,
applications.
Frank Guenther
Associate Professor of Cognitive and Neural Systems
PhD, Cognitive and Neural Systems, Boston University
MSE, Electrical Engineering, Princeton University
Speech production, speech perception, biological sensory-motor control and
functional brain imaging.
Catherine L. Harris
Assistant Professor of Psychology
PhD, Cognitive Science and Psychology, University of California at San Diego
Visual word recognition, psycholinguistics, cognitive semantics,
second language acquisition, computational models of cognition.
Michael E. Hasselmo
Associate Professor of Psychology
Director of Graduate Studies, Psychology Department
PhD, Experimental Psychology, Oxford University
Electrophysiological studies of neuromodulatory effects in cortical
structures, network biophysical simulations of memory function in
hippocampus and piriform cortex, behavioral studies of amnestic drugs.
Thomas G. Kincaid
Professor of Electrical, Computer and Systems Engineering, College of
Engineering
PhD, Electrical Engineering, Massachusetts Institute of Technology
Signal and image processing, neural networks, non-destructive testing.
Mark Kon
Professor of Mathematics
PhD, Massachusetts Institute of Technology
Neural network theory, complexity theory, wavelet theory, mathematical
physics.
Nancy Kopell
Professor of Mathematics
PhD, Mathematics, University of California at Berkeley
Dynamics of networks of neurons.
Jacqueline A. Liederman
Associate Professor of Psychology
PhD, Psychology, University of Rochester
Dynamics of interhemispheric cooperation; prenatal correlates of neuro-
developmental disorders.
Ennio Mingolla
Professor of Cognitive and Neural Systems and Psychology
PhD, Psychology, University of Connecticut
Visual perception, mathematical modeling of visual processes.
Joseph Perkell
Adjunct Professor of Cognitive and Neural Systems
Senior Research Scientist, Research Lab of Electronics and Department of
Brain and Cognitive Sciences, Massachusetts Institute of Technology
PhD, Massachusetts Institute of Technology
Motor control of speech production.
Alan Peters
Professor of Anatomy and Neurobiology, School of Medicine
PhD, Zoology, Bristol University, United Kingdom
Organization of neurons in the cerebral cortex; effects of aging on
the primate brain; fine structure of the nervous system.
Andrzej Przybyszewski
Research Fellow, Department of Cognitive and Neural Systems
Assistant Professor, University of Massachusetts Medical School, Worcester
PhD, Warsaw Medical Academy
Electrophysiology of the primate visual system, mathematical and computer
modeling of the neuronal networks in the visual system.
Adam Reeves
Adjunct Professor of Cognitive and Neural Systems
Professor of Psychology, Northeastern University
PhD, Psychology, City University of New York
Psychophysics, cognitive psychology, vision.
Mark Rubin
Research Fellow, Department of Cognitive and Neural Systems
Staff Member, Sensor Exploitation Group, MIT Lincoln Laboratory
PhD, Physics, University of Chicago
Pattern recognition; artificial and biological vision.
Michele Rucci
Assistant Professor of Cognitive and Neural Systems
PhD, Scuola Superiore, Pisa, Italy
Vision, sensory-motor control and learning, and computational neuroscience.
Elliot Saltzman
Associate Professor of Physical Therapy, Sargent College
Research Scientist, Haskins Laboratories, New Haven, CT
Assistant Professor in Residence, Department of Psychology and Center for
the Ecological Study of Perception and Action, University of Connecticut,
Storrs, CT
PhD, Developmental Psychology, University of Minnesota
Modeling and experimental studies of human sensorimotor control and
coordination of the limbs and speech articulators, focusing on issues
of timing in skilled activities.
Robert Savoy
Adjunct Associate Professor of Cognitive and Neural Systems
Scientist, Rowland Institute for Science
Experimental Psychologist, Massachusetts General Hospital
PhD, Experimental Psychology, Harvard University
Computational neuroscience; visual psychophysics of color, form, and motion
perception. Teaching about functional MRI and other brain mapping methods.
Eric Schwartz
Professor of Cognitive and Neural Systems; Electrical, Computer and Systems
Engineering; and Anatomy and Neurobiology
PhD, High Energy Physics, Columbia University
Computational neuroscience, machine vision, neuroanatomy, neural modeling.
Robert Sekuler
Adjunct Professor of Cognitive and Neural Systems
Research Professor of Biomedical Engineering, College of Engineering,
BioMolecular Engineering Research Center
Frances and Louis H. Salvage Professor of Psychology, Brandeis University
Consultant in neurosurgery, Boston Children's Hospital
PhD, Psychology, Brown University
Visual motion, brain imaging, relation of visual perception, memory, and
movement.
Barbara Shinn-Cunningham
Assistant Professor of Cognitive and Neural Systems and Biomedical
Engineering
PhD, Electrical Engineering and Computer Science, Massachusetts Institute
of Technology
Psychoacoustics, audition, auditory localization, binaural hearing,
sensorimotor adaptation, mathematical models of human performance.
Malvin Teich
Professor of Electrical and Computer Engineering, Biomedical Engineering,
and Physics
PhD, Cornell University
Quantum optics and imaging, photonics, wavelets and fractal stochastic
processes, biological signal processing and information transmission.
Lucia Vaina
Professor of Biomedical Engineering
Research Professor of Neurology, School of Medicine
PhD, Sorbonne (France); Dres Science, National Politechnique Institute,
Toulouse (France)
Computational visual neuroscience, biological and computational learning,
functional
and structural neuroimaging.
Faramarz Valafar
Adjunct Assistant Professor of Cognitive and Neural Systems
PhD, Electrical Engineering, Purdue University
Bioinformatics, adaptive systems (artificial neural networks), data mining
and
modeling in medicine, medical decision making, pattern recognition and
signal
processing in biomedicine, biochemistry, and glycoscience.
Takeo Watanabe
Associate Professor of Psychology
PhD, Behavioral Sciences, University of Tokyo
Perception of objects and motion and effects of attention on perception
using
psychophysics and brain imaging (f-MRI).
Allen Waxman
Adjunct Associate Professor of Cognitive and Neural Systems
Senior Staff Scientist, MIT Lincoln Laboratory
PhD, Astrophysics, University of Chicago
Visual system modeling, multisensor fusion, image mining, parallel
computing,
and advanced visualization.
Jeremy Wolfe
Adjunct Associate Professor of Cognitive and Neural Systems
Associate Professor of Ophthalmology, Harvard Medical School
Psychophysicist, Brigham & Women's Hospital, Surgery Dept.
Director of Psychophysical Studies, Center for Clinical Cataract Research
PhD, Massachusetts Institute of Technology
Visual attention, preattentive and attentive object representation.
Curtis Woodcock
Professor of Geography
Director, Geographic Applications, Center for Remote Sensing
PhD, University of California, Santa Barbara
Biophysical remote sensing, particularly of forests and natural vegetation,
canopy reflectance models and their inversion, spatial modeling, and change
detection; biogeography; spatial analysis; geographic information systems;
digital image processing.
CNS DEPARTMENT COURSE OFFERINGS
CAS CN500 Computational Methods in Cognitive and Neural Systems
CAS CN510 Principles and Methods of Cognitive and Neural Modeling I
CAS CN520 Principles and Methods of Cognitive and Neural Modeling II
CAS CN530 Neural and Computational Models of Vision
CAS CN540 Neural and Computational Models of Adaptive Movement Planning
and Control
CAS CN550 Neural and Computational Models of Recognition, Memory and
Attention
CAS CN560 Neural and Computational Models of Speech Perception and
Production
CAS CN570 Neural and Computational Models of Conditioning, Reinforcement,
Motivation and Rhythm
CAS CN580 Introduction to Computational Neuroscience
GRS CN700 Computational and Mathematical Methods in Neural Modeling
GRS CN720 Neural and Computational Models of Planning and Temporal
Structure
in Behavior
GRS CN730 Models of Visual Perception
GRS CN740 Topics in Sensory-Motor Control
GRS CN760 Topics in Speech Perception and Recognition
GRS CN780 Topics in Computational Neuroscience
GRS CN810 Topics in Cognitive and Neural Systems: Visual Event Perception
GRS CN811 Topics in Cognitive and Neural Systems: Visual Perception
GRS CN911,912
Research in Neural Networks for Adaptive Pattern Recognition
GRS CN915,916
Research in Neural Networks for Vision and Image Processing
GRS CN921,922
Research in Neural Networks for Speech and Language Processing
GRS CN925,926
Research in Neural Networks for Adaptive Sensory-Motor Planning
and Control
GRS CN931,932
Research in Neural Networks for Conditioning and Reinforcement Learning
GRS CN935,936
Research in Neural Networks for Cognitive Information Processing
GRS CN941,942
Research in Nonlinear Dynamics of Neural Networks
GRS CN945,946
Research in Technological Applications of Neural Networks
GRS CN951,952
Research in Hardware Implementations of Neural Networks
CNS students also take a wide variety of courses in related departments.
In addition, students participate in a weekly colloquium series, an informal
lecture series, and student-run special interest groups, and attend lectures
and meetings throughout the Boston area; and advanced students work in small
research groups.
LABORATORY AND COMPUTER FACILITIES
The department is funded by fellowships, grants, and contracts from federal
agencies and private foundations that support research in life sciences,
mathematics, artificial intelligence, and engineering. Facilities include
laboratories for experimental research and computational modeling in
visual perception; audition, speech and language processing; and
sensory-motor control and robotics. Data analysis and numerical
simulations are carried out on a state-of-the-art computer network
comprised of Sun workstations, Silicon Graphics workstations, Macintoshes,
and PCs. A PC farm running Linux operating systems is available as a
distributed computational environment. All students have access to
X-terminals or UNIX workstation consoles, a selection of color systems and
PCs, a network of SGI machines, and standard modeling and mathematical
simulation packages such as Mathematica, VisSim, Khoros, and Matlab.
The department maintains a core collection of books and journals, and has
access both to the Boston University libraries and to the many other
collections of the Boston Library Consortium.
In addition, several specialized facilities and software are available for
use. These include:
Computer Vision/Computational Neuroscience Laboratory
The Computer Vision/Computational Neuroscience Lab is comprised of an
electronics workshop, including a surface-mount workstation, PCD
fabrication tools, and an Alterra EPLD design system; a light machine
shop; an active vision lab including actuators and video hardware; and
systems for computer aided neuroanatomy and application of computer
graphics and image processing to brain sections and MRI images.
Neurobotics Laboratory
The Neurobotics Lab utilizes wheeled mobile robots to study potential
applications of neural networks in several areas, including adaptive
dynamics and kinematics, obstacle avoidance, path planning and navigation,
visual object recognition, and conditioning and motivation. The lab
currently has three Pioneer robots equipped with sonar and visual sensors;
one B-14 robot with a moveable camera, sonars, infrared, and bump sensors;
and two Khepera miniature robots with infrared proximity detectors. Other
platforms may be investigated in the future.
Psychoacoustics Laboratory
The Psychoacoustics Lab houses a newly installed, 8 ft. x 8 ft. sound-proof
booth. The laboratory is extensively equipped to perform both traditional
psychoacoustic experiments and experiments using interactive auditory
virtual-reality stimuli. The major equipment dedicated to the
psychoacoustics laboratory includes two Pentium-based personal computers;
two Power-PC-based Macintosh computers; a 50-MHz array processor capable
of generating auditory stimuli in real time; programmable attenuators;
analog-to-digital and digital-to-analog converters; a real-time head
tracking system; a special-purpose, signal-processing hardware system
capable of generating "spatialized" stereo auditory signals in real time;
a two-channel oscilloscope; a two-channel spectrum analyzer; various
cables, headphones, and other miscellaneous electronics equipment; and
software for signal generation, experimental control, data analysis, and
word processing.
Sensory-Motor Control Laboratory
The Sensory-Motor Control Lab supports experimental studies of motor
kinematics. An infrared WatSmart system allows measurement of large-scale
movements, and a pressure-sensitive graphics tablet allows studies of
handwriting and other fine-scale movements. Equipment includes a 40-inch
monitor that allows computer display of animations generated by an SGI
workstation or a Pentium Pro (Windows NT) workstation. A second major
component is a helmet-mounted, video-based, eye-head tracking system
(ISCAN Corp, 1997). The latter's camera samples eye position at 240Hz and
also allows reconstruction of what subjects are attending to as they
freely scan a scene under normal lighting. Thus the system affords a wide
range of visuo-motor studies.
Speech and Language Laboratory
The Speech and Language Lab includes facilities for analog-to-digital and
digital-to-analog software conversion. Ariel equipment allows reliable
synthesis and playback of speech waveforms. An Entropic signal processing
package provides facilities for detailed analysis, filtering, spectral
construction, and formant tracking of the speech waveform. Various large
databases, such as TIMIT and TIdigits, are available for testing
algorithms of speech recognition. For high speed processing,
supercomputer facilities speed filtering and data analysis.
Visual Psychophysics Laboratory
The Visual Psychophysics Lab occupies an 800-square-foot suite, including
three dedicated rooms for data collection, and houses a variety of
computer controlled display platforms, including Silicon Graphics, Inc.
(SGI) Onyx RE2, SGI Indigo2 High Impact, SGI Indigo2 Extreme, Power
Computing (Macintosh compatible) PowerTower Pro 225, and Macintosh 7100/66
workstations. Ancillary resources for visual psychophysics include a
computer-controlled video camera, stereo viewing glasses, prisms, a
photometer, and a variety of display-generation, data-collection, and
data-analysis software.
Affiliated Laboratories
Affiliated CAS/CNS faculty have additional laboratories ranging from visual
and auditory psychophysics and neurophysiology, anatomy, and
neuropsychology to engineering and chip design. These facilities are used
in the context of faculty/student collaborations.
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DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS
GRADUATE TRAINING ANNOUNCEMENT
Boston University
677 Beacon Street
Boston, MA 02215
Phone: 617/353-9481
Fax: 617/353-7755
Email: inquiries@cns.bu.edu
Web: http://www.cns.bu.edu/
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