Human-competitive applications of
evolutionary computation: Evolutionary computation systems
have
recently become sufficiently powerful to rival human performance on
real-world applications in a variety of areas of science and
engineering. Work by Profesor Spector and his collaborators in this
area has produced human-competitive results in the areas of quantum
computing and mathematics, and has twice won the gold medal in the Human
Competitive Results contest of the Genetic and Evolutionary
Computation Conference (2008
press release, 2004
information). For more information search for the human-competitive tag on the publications
page.
Evolutionary computation with the
Push
programming language: Push is a programming language
designed
for evolutionary computation, to be used as the programming language
within which evolving programs are expressed. Push-based
evolutionary
computation systems have a variety of desirable features, including
the
ability to evolve programs that use multiple data types, modular
architechtures, and recursion. Push also supports novel forms of
"ontogenetic" or developmental genetic programming,
meta-evolutionary
systems (in which the evolutionary algorithm itself evolves), and
automatic program simplification. For more information see the Push project page
or search for the push tag
on
the publications
page.
Automatic quantum computer
programming:
Once realized, the potential of large-scale quantum computers
promises
to radically transform computer science. Despite large-scale
international efforts, however, essential questions about the
potential
of quantum algorithms are still unanswered. This project explores
several ways in which evolutionary computation technology can be
used
to automatically program quantum computers and thereby to contribute
to
our understanding of quantum computation. For more information
search
for the quantum tag on the
publications
page.
Evolutionary dynamics:
Computational simulations can be used to study a wide range of
questions about the dynamics of genes and behaviors in evolving
populations. Work by Professor Spector and his collaborators in this
area
has addressed the evolution of altruism, cooperation, teamwork,
coordination, and diversity, questions about the use of
mitochondrial
DNA to determine species origins and divergence times, and measures
of
evolutionary activity. For more information search for the evolutionary dynamics tag on the
publications
page.
Origins of adaptive complexity:
Digital technologies provide new ways to ask and potentially to
answer
questions about the ways in which life and other complex adaptive
systems can arise from simpler constituents. Work by Professor
Spector
and his collaborators in this area has included experiments with
open-ended evolution of development, form and behavior (as in Division
Blocks),
investigations of the ways that certain behaviors can arise by
natural
selection, and the development of a framework called
"autoconstructive
evolution" in which the mechanisms of reproduction and
diversification
are themselves evolved within an evolutionary computation system.
For
more information search for the artificial
life tag on the publications
page.
Artificial intelligence, creativity
and the arts: Artificial intelligence technology provides
novel
tools for the investigation of human creativity and for the
production
of new modes of expressions. Work by Professor Spector and his
collaborators in this area has focused on the production of music
and
art from evolutionary and adaptive systems. For more information
search
for the arts tag on the publications
page and see the Computational
Creativity Curriculum.
Human and machine cognition:
Artificial intelligence technologies and theories provide a rich
array
of tools and conceptual frameworks with which researchers can
approach
fundamental questions in cognitive science. Work by Professor
Spector
and his collaborators in this area has focused on human and machine
action planning and execution, knowledge representation, and the
ways
in which cognitive systems can arise by natural selection. For more
information search for the cognition
tag on the publications
page.
Technological infrastructure for AI
research: Research in artificial intelligence often relies
on
the prior development of new software technologies to support
specific types of computations. Work by Professor Spector and his
collaborators in this area has focused on the development of
simulation
systems (such as breve)
and frameworks for using networked computers in novel ways, for
example
with "unwitting"
or
parasitic computing. For more information search for the instrumentation tag on the publications
page.
Artificial intelligence and
education:
Artificial intelligence technology can be used to enhance education
in
a variety of fields, and the study of artificial intelligence can
help
to integrate computer science with other disciplines. For more
information on the work of Professor Spector and his collaborators
in
this area search for the education
tag on the publications
page.
The Creative
Cognition Laboratory (no longer active
although related projects are still supported).
WWW development projects:
What About AIDS? Website and CD-ROM development with the
New
York Hall of Science
"School/College Partnerships: Inquiry-Based Science and
Technology for All Students and Teachers," edited by Merle
S. Bruno and
Jaqueline Nocella Chase
