physics

Norman Packard

Norman Packard is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Norman Packard rather than just read about it. In short: Norman Harry Packard (born 1954 in Billings, Montana) is a chaos theory physicist and one of the founders of the Prediction Company and ProtoLife. He is an alumnus of Reed College, with a PhD from the University of California, Santa Cruz.

Key takeaways

Norman Packard belongs to physics; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Norman Packard to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Norman Packard from memory before moving on to harder problems.

Reference excerpt

Norman Harry Packard (born 1954 in Billings, Montana) is a chaos theory physicist and one of the founders of the Prediction Company and ProtoLife. He is an alumnus of Reed College, with a PhD from the University of California, Santa Cruz. Packard is known for his contributions to chaos theory, complex systems, and artificial life. He coined the phrase "the edge of chaos".

Biography Between 1976 and 1981, Packard formed the Dynamical Systems Collective at UC Santa Cruz with fellow physics graduate students, Rob Shaw, Doyne Farmer, and James Crutchfield. The collective was best known for its work in probing chaotic systems for signs of order. Around the same time, he worked with Doyne Farmer and other friends in Santa Cruz, California to form the Eudaemons collective, to develop a strategy for beating the roulette wheel using a toe-operated computer. The computer could, in theory, predict in what area a roulette ball would land on a wheel, giving the player a significant statistical advantage over the house. Although the project itself was a success, they ran into practical difficulty employing the technique on-site in Las Vegas casinos. The experiences of Norman, Doyne Farmer, and crew were later chronicled in the book The Eudaemonic Pie (1985) by Thomas Bass. Their experience was also chronicled on the History Channel television series "Breaking Vegas." In 1982, Packard won a NATO post-doctoral fellowship to study at the Institut des Hautes Études Scientifiques in Bures-sur-Yvette, France. One year later, he joined the Princeton Institute for Advanced Study. At the IAS, he worked with colleagues Stephen Wolfram and Rob Shaw to explain complex systems and the tendency for matter to organize itself. Subsequently, Packard has made contributions to the field of Artificial Life, including the definition of Evolutionary Activity.

Professional work

Center for Complex Systems Research In 1985 Packard moved with Wolfram to the physics department of the University of Illinois, where they founded the Center for Complex Systems Research.

Santa Fe Institute Packard was involved with the Santa Fe Institute over many years, serving in several capacities including External Professor and member of the chair of the Science Steering Committee.

Prediction Company In the spring of 1985, Packard and Doyne Farmer realized that their research in fields such as chaos, Genetic Algorithms and cellular automata could help build a system for predicting the stock market. Five years later they founded Prediction Company, a small company in Santa Fe, NM dedicated to making a model for predicting what a market would do during a certain time period. A brief outline of some of the genetic algorithm techniques he used in the early days is presented in chapter 2 of reference 5 below. In 2004, Prediction Company received the "Employer of Choice" award in the small size category for the State of New Mexico. Prediction Company was eventually acquired by UBS.

European Center for Living Technology In 2004, Packard was one of the founders of the European Centre for Living Technology (ECLT), hosted by the University of Venice, Ca' Foscari. The ECLT received its first funding from PACE (Programmable Artificial Cell Evolution), a project coordinated by John S. McCaskill and funded by the European Union. From its inception in 2004 and for over a decade Packard has served on its science board, and as co-director.

ProtoLife While in Venice, Packard founded ProtoLife, the first company to capitalize on living technology. The goal of the company is to optimize complex chemical reactions and other complex processes. The company was launched in Venice, Italy, and is currently based in San Francisco having changed name to Daptics (see below).

Lucky Sort In 2011 Packard joined Lucky Sort as Chief Science Officer. At Lucky Sort he guides research to discover and display structure in high volume text data streams. Lucky Sort was eventually acquired by Twitter.

Daptics In 2018, Packard launched a web-based optimization and discovery tool on the internet (a form of Software as a Service), changing the company name from ProtoLife to Daptics, to better reflect its new focus. The goal of the company is to optimize complex chemical reactions and other complex processes. The company is currently based in San Francisco.

Books Artificial Life VII, with Mark A. Bedau, John S. McCaskill, Steen Rasmussen. 2000 Protocells, with Steen Rasmussen, Mark Bedau, Liaohai Chen, David Deamer, David Krakauer, and Peter Stadler ‘’Adaptation Toward the Edge of Chaos’’, Norman H. Packard, University of Illinois at Urbana-Champaign, Center for Complex Systems Research, 1988

Illustrations

Worked examples

Example 1 — a first encounter with Norman Packard

Start with the simplest possible case. Write down what Norman Packard claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Norman Packard before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Norman Packard ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Norman Packard

In research: Norman Packard appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Norman Packard in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Norman Packard is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1954 births, 21st-century American physicists, Cellular automatists, so understanding it makes those chapters shorter.
In everyday life: Look for Norman Packard outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Norman Packard in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Norman Packard means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Norman Packard out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Norman Packard in simple terms?

Why does Norman Packard matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Norman Packard?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Norman Packard.