Lee Spector: Projects

Project areas

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.

Project-related code

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Selected presentation slides and materials

Old projects

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