computer science

Inman Harvey

Inman Harvey is a computer science 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 Inman Harvey rather than just read about it. In short: Inman Harvey (died 5 June 2026) was a British computer scientist and academic who was a senior lecturer in computer science and artificial intelligence at the University of Sussex; he later was a visiting senior research fellow at the same university. His research interests largely centered on the development of artificial evolution as an approach to the design of complex systems.

Key takeaways

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

Reference excerpt

Inman Harvey (died 5 June 2026) was a British computer scientist and academic who was a senior lecturer in computer science and artificial intelligence at the University of Sussex; he later was a visiting senior research fellow at the same university. His research interests largely centered on the development of artificial evolution as an approach to the design of complex systems. Application domains of interest included evolutionary robotics, evolvable hardware, molecules for pharmaceutical purposes. Together with other Sussex faculty, mainly from the School of Cognitive and Computer Sciences (COGS), he developed the MSc programme on Evolutionary and Adaptive Systems (EASy), which was active in the 1990s and 2000s, attracting dozens of students that have contributed to artificial life, evolutionary robotics, cognitive science and other disciplines. Harvey's other interests included philosophical approaches to AI and artificial life (a non-representational, dynamical systems approach); passive dynamic walking; and Gaia theory. He originally started as a mathematician and philosopher at the University of Cambridge. The article "Evolving a Conscious Machine" in the June 1998 issue of the magazine Discover (pp. 72–79) overviews Harvey's and Adrian Thompson's work with evolving an FPGA program to recognize tones. See: Harvey died on 5 June 2026.

Selected publications Harvey's highest-cited papers indexed at Google Scholar are:

N. Jakobi, P. Husbands, I. Harvey (1995). Noise and the reality gap: The use of simulation in evolutionary robotics. Advances in Artificial Life: Third European Conference on Artificial Life D. Cliff, P. Husbands, I. Harvey (1993). Explorations in evolutionary robotics. Adaptive Behavior 2 (1): 73–110 I. Harvey, P. Husbands, D. Cliff, A. Thompson, N. Jakobi (1997). Evolutionary robotics: the Sussex approach. Robotics and Autonomous Systems 20 (2–4), 205–24

References

External links University of Sussex profile Google Scholar profile

Worked examples

Example 1 — a first encounter with Inman Harvey

Start with the simplest possible case. Write down what Inman Harvey claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, 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 Inman Harvey 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 Inman Harvey 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 Inman Harvey

In research: Inman Harvey appears in computer science 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 Inman Harvey 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: Inman Harvey is common in secondary-school and first-year university syllabi. It links to neighbouring topics 2026 deaths, 20th-century births, Academics of the University of Sussex, so understanding it makes those chapters shorter.
In everyday life: Look for Inman Harvey 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 Inman Harvey in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Inman Harvey 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 Inman Harvey out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Inman Harvey in simple terms?

Why does Inman Harvey matter?

Because it connects several computer science 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 Inman Harvey?

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 Inman Harvey.