John Henry Holland

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John Henry Holland
John Henry Holland.jpg
Born(1929-02-02)February 2, 1929
Fort Wayne, Indiana
Died August 9, 2015(2015-08-09) (aged 86)
Ann Arbor, Michigan
Alma mater University of Michigan
Known for Research on genetic algorithms
Awards MacArthur Fellow (1992)
Harold Pender Award (1999)
Fellow of the World Economic Forum
Scientific career
Fields Complex systems
Psychology
Electrical engineering
Computer science
Institutions University of Michigan
Santa Fe Institute
Doctoral advisor Arthur Walter Burks
Doctoral students

Edgar Codd [1]

Melanie Mitchell [2]

John Henry Holland (February 2, 1929 – August 9, 2015) was an American scientist and Professor of psychology and Professor of electrical engineering and computer science at the University of Michigan, Ann Arbor. He was a pioneer in what became known as genetic algorithms.

Psychology is the science of behavior and mind. Psychology includes the study of conscious and unconscious phenomena, as well as feeling and thought. It is an academic discipline of immense scope. Psychologists seek an understanding of the emergent properties of brains, and all the variety of phenomena linked to those emergent properties. As a social science it aims to understand individuals and groups by establishing general principles and researching specific cases.

Electrical engineering field of engineering that deals with electricity

Electrical engineering is a professional engineering discipline that generally deals with the study and application of electricity, electronics, and electromagnetism. This field first became an identifiable occupation in the later half of the 19th century after commercialization of the electric telegraph, the telephone, and electric power distribution and use. Subsequently, broadcasting and recording media made electronics part of daily life. The invention of the transistor, and later the integrated circuit, brought down the cost of electronics to the point they can be used in almost any household object.

Computer science Study of the theoretical foundations of information and computation

Computer science is the study of processes that interact with data and that can be represented as data in the form of programs. It enables the use of algorithms to manipulate, store, and communicate digital information. A computer scientist studies the theory of computation and the practice of designing software systems.

Contents

Biography

Holland was born in Fort Wayne, Indiana, in 1929. He studied physics at the Massachusetts Institute of Technology and received a B.S. degree in 1950, then studied Mathematics at the University of Michigan, receiving an M.A. in 1954. [3] In 1959 he received the first computer science Ph.D. from the University of Michigan. He was a Professor of psychology and Professor of electrical engineering and computer science at the University of Michigan, Ann Arbor. He held visiting positions at the Rowland Institute for Science and the University of Bergen.

Massachusetts Institute of Technology University in Massachusetts

The Massachusetts Institute of Technology (MIT) is a private research university in Cambridge, Massachusetts. Founded in 1861 in response to the increasing industrialization of the United States, MIT adopted a European polytechnic university model and stressed laboratory instruction in applied science and engineering. The Institute is a land-grant, sea-grant, and space-grant university, with a campus that extends more than a mile alongside the Charles River. Its influence in the physical sciences, engineering, and architecture, and more recently in biology, economics, linguistics, management, and social science and art, has made it one of the most prestigious universities in the world. MIT is often ranked among the world's top universities.

A Bachelor of Science is an undergraduate academic degree awarded for completed courses that generally last three to five years, or a person holding such a degree.

University of Michigan Public research university in Ann Arbor, Michigan, United States

The University of Michigan, often simply referred to as Michigan, is a public research university in Ann Arbor, Michigan. The university is Michigan's oldest; it was founded in 1817 in Detroit, as the Catholepistemiad, or University of Michigania, 20 years before the territory became a state. The school was moved to Ann Arbor in 1837 onto 40 acres (16 ha) of what is now known as Central Campus. Since its establishment in Ann Arbor, the university campus has expanded to include more than 584 major buildings with a combined area of more than 34 million gross square feet spread out over a Central Campus and North Campus, two regional campuses in Flint and Dearborn, and a Center in Detroit. The university is a founding member of the Association of American Universities.

Holland was a member of the Board of Trustees and Science Board of the Santa Fe Institute and a fellow of the World Economic Forum. [4]

Santa Fe Institute non-profit organisation in the USA

The Santa Fe Institute (SFI) is an independent, nonprofit theoretical research institute located in Santa Fe and dedicated to the multidisciplinary study of the fundamental principles of complex adaptive systems, including physical, computational, biological, and social systems. As of 2016, the Institute is ranked 20th among the world's "Top Science and Technology Think Tanks" and 23rd among the world's "Best Transdisciplinary Research Think Tanks" according to the Global Think Tank Report published annually by the University of Pennsylvania.

World Economic Forum Swiss non-profit foundation

The World Economic Forum (WEF), based in Cologny-Geneva, Switzerland, was founded in 1971 as a not-for-profit organization. It gained formal status in January 2015 under the Swiss Host-State Act, confirming the role of the Forum as an International Institution for Public-Private Cooperation. The Forum's mission is cited as "committed to improving the state of the world by engaging business, political, academic, and other leaders of society to shape global, regional, and industry agendas".

Holland received the 1961 Louis E. Levy Medal from The Franklin Institute, and the MacArthur Fellowship in 1992. [5] [6]

He was profiled extensively in chapters 5 and 7 of the book Complexity (1993), by M. Mitchell Waldrop.

Holland died on August 9, 2015 in Ann Arbor, Michigan. [7]

Work

Holland frequently lectured around the world on his own research, and on research and open questions in complex adaptive systems (CAS) studies. In 1975 he wrote the ground-breaking book on genetic algorithms, "Adaptation in Natural and Artificial Systems". He also developed Holland's schema theorem.

Holland's schema theorem, also called the fundamental theorem of genetic algorithms, is an inequality that results from coarse-graining an equation for evolutionary dynamics. The Schema Theorem says that short, low-order schemata with above-average fitness increase exponentially in frequency in successive generations. The theorem was proposed by John Holland in the 1970s. It was initially widely taken to be the foundation for explanations of the power of genetic algorithms. However, this interpretation of its implications has been criticized in several publications reviewed in, where the Schema Theorem is shown to be a special case of the Price equation with the schema indicator function as the macroscopic measurement.

Publications

Holland is the author of a number of books about complex adaptive systems, including:

Articles, a selection:

Related Research Articles

Complexity characterises the behaviour of a system or model whose components interact in multiple ways and follow local rules, meaning there is no reasonable higher instruction to define the various possible interactions.

Genetic algorithm competitive algorithm for searching a problem space

In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on bio-inspired operators such as mutation, crossover and selection. John Holland introduced genetic algorithms in 1960 based on the concept of Darwin’s theory of evolution; afterwards, his student David E. Goldberg extended GA in 1989.

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Robert Sedgewick is an American computer science professor at Princeton University and a member of the board of directors of Adobe Systems.

Evolutionary computation Trial and error problem solvers with a metaheuristic or stochastic optimization character

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Bio-inspired computing, short for biologically inspired computing, is a field of study that loosely knits together subfields related to the topics of connectionism, social behaviour and emergence. It is often closely related to the field of artificial intelligence, as many of its pursuits can be linked to machine learning. It relies heavily on the fields of biology, computer science and mathematics. Briefly put, it is the use of computers to model the living phenomena, and simultaneously the study of life to improve the usage of computers. Biologically inspired computing is a major subset of natural computation.

In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, or select a heuristic that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity. Metaheuristics sample a set of solutions which is too large to be completely sampled. Metaheuristics may make few assumptions about the optimization problem being solved, and so they may be usable for a variety of problems.

Computational sociology branch of sociology that uses computational methods to study social phenomena

Computational sociology is a branch of sociology that uses computationally intensive methods to analyze and model social phenomena. Using computer simulations, artificial intelligence, complex statistical methods, and analytic approaches like social network analysis, computational sociology develops and tests theories of complex social processes through bottom-up modeling of social interactions.

Artificial society is the specific agent based computational model for computer simulation in social analysis. It is mostly connected to the theme in complex system, emergence, Monte Carlo method, computational sociology, multi-agent system, and evolutionary programming. The concept itself is simple enough. Actually reaching this conceptual point took a while. Complex mathematical models have been, and are, common; deceivingly simple models only have their roots in the late forties, and took the advent of the microcomputer to really get up to speed.

Christopher Langton American computer scientist

Christopher Gale Langton is an American computer scientist and one of the founders of the field of artificial life. He coined the term in the late 1980s when he organized the first "Workshop on the Synthesis and Simulation of Living Systems" at the Los Alamos National Laboratory in 1987. Following his time at Los Alamos, Langton joined the Santa Fe Institute (SFI), to continue his research on artificial life. He left SFI in the late 1990s, and abandoned his work on artificial life, publishing no research since that time.

A complex adaptive system is a system in which a perfect understanding of the individual parts does not automatically convey a perfect understanding of the whole system's behavior. The study of complex adaptive systems, a subset of nonlinear dynamical systems, is highly interdisciplinary and blends insights from the natural and social sciences to develop system-level models and insights that allow for heterogeneous agents, phase transition, and emergent behavior.

Melanie Mitchell is a professor of computer science at Portland State University. She has worked at the Santa Fe Institute and Los Alamos National Laboratory. Her major work has been in the areas of analogical reasoning, Complex Systems, genetic algorithms and cellular automata, and her publications in those fields are frequently cited.

David Edward Goldberg is an American computer scientist, civil engineer, and professor at the department of Industrial and Enterprise Systems Engineering (IESE) at the University of Illinois at Urbana-Champaign and is most noted for his work in the field of genetic algorithms. He is the director of the Illinois Genetic Algorithms Laboratory (IlliGAL) and the chief scientist of Nextumi Inc. He is the author of Genetic Algorithms in Search, Optimization and Machine Learning, one of the most cited books in computer science.

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Scott E. Page is an American social scientist and Leonid Hurwicz Collegiate Professor of Complex Systems, Political Science, and Economics at the University of Michigan, Ann Arbor, where he has been working since 2000. He has also been director of the Center for the Study of Complex Systems at the University of Michigan (2009-2014) and an external faculty member at the Santa Fe Institute.

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References