astronomy

Ryszard S. Michalski

Ryszard S. Michalski is a astronomy 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 Ryszard S. Michalski rather than just read about it. In short: Ryszard Stanisław Michalski (May 7, 1937 – September 20, 2007) was a Polish-American computer scientist. Michalski was Professor at George Mason University and a pioneer in the field of machine learning.

Key takeaways

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

Reference excerpt

Ryszard Stanisław Michalski (May 7, 1937 – September 20, 2007) was a Polish-American computer scientist. Michalski was Professor at George Mason University and a pioneer in the field of machine learning.

Biography Michalski was born in Kalusz near Lvov on 7 May 1937. He received an equivalent of Bachelor of Science degree in Electrical Engineering at the Universities of Technology in Kraków and Warsaw in 1959; obtained M.S. Computer Science at the Polytechnic Institute of St. Petersburg in 1961; and Ph.D. in Computer Science at the Silesian University of Technology, Gliwice in 1969. In the period 1962–1970 he worked at the Institute of Automation of the Polish Academy of Sciences (PAS) in Warsaw, during which he and Jacek Karpiński developed an early successful learning system for recognizing handwritten alpha-numeric characters. He emigrated to America in 1970, worked at the University of Illinois at Urbana-Champaign until moved with his research group to the George Mason University in 1988. Although leaving Poland, he worked part-time at the Institute of Computer Science of PAS in Warsaw. Ryszard S. Michalski died on 20 September 2007 from cancer at his home in Fairfax.

Academic life Michalski was cofounder of Machine Learning and Inference Laboratory at George Mason University. He earned a patent for the university with Learnable Non-Darwinian Evolution Model (LEM), a form of evolutionary computation, in 2003. He cofounded the Journal of Machine Learning in 1986 and helped organize the first international multistrategy machine learning conferences in 1991.

Work Michalski influenced wide areas, notably in machine learning, but also in the broadly understood areas of data analysis and knowledge discovery. Some of his offspring are listed below. (See more on his homepage at GMU.)

Learning system for handwritten character recognition (1966) AQ algorithm (1969) Conceptual clustering (1980) Multistrategy learning (1984) Logic of human plausible reasoning-with Alan Collins (1979–1989) Multistrategy data mining/Knowledge segment (1991) Data-driven constructive induction (1991) Hypothesis-driven constructive induction (1991) Inferential theory of learning (1991) Learning trees from rules (1993) Natural induction (1996) Learnable Evolution Model-LEM (1997) Data Inferencing (1998) Knowledge Mining (2001) Attributional calculus (1998/2004)

Honors and awards Michalski was elected to Foreign Member of the Polish Academy of Sciences in 2000 and Fellow of AAAI. Poland President honored him with the Officer's Cross of the Order of Merit of the Republic of Poland in July 2007.

Selected works Michalski was prolific author of scientific works on various topics in computer science, including machine learning, artificial intelligence, and human plausible reasoning. He wrote, co-wrote, or co-edited more than 350 research publications and more than one dozen books. Some of which are listed below. (See more on his homepage at GMU.)

Books 1983. (with Jaime Carbonell & Tom M. Mitchell, Eds.) Machine learning: An artificial intelligence approach. Los Altos, CA: Morgan Kaufmann. 1986. (with J.G. Carbonell & Tom Mitchell, Eds.) Machine learning: An artificial intelligence approach. Vol. II. Los Altos, CA: Morgan-Kaufmann. 1986. (with Tom Mitchell & J. Carbonell, Eds.) Machine Learning: A Guide to Current Research. Kluwer Academic Publishers. 1990. (with Kodratoff, Y, Eds.) Machine learning: An artificial intelligence approach. Vol. III. Los Altos, CA: Morgan-Kaufmann. 1993. Multistrategy Learning: A Special Issue of MACHINE LEARNING. Springer. 1994. (with George Tecuci, Eds) Machine Learning: A Multistrategy Approach, Volume IV. Morgan Kaufmann 1998. (with Ivan Bratko & Miroslav Kubat, Eds.) Machine Learning and Data Mining: Methods and Applications. Wiley

Articles 1980. Pattern recognition as rule-guided inductive inference. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2, 349–361. 1980. Knowledge Acquisition Through Conceptual Clustering: A Theoretical Framework and an Algorithm for Partitioning Data into Conjunctive Concepts. Journal of Policy Analysis and Information Systems. 4. 219-244. 1986. (with Pat Langley) Editorial: Machine Learning and Discovery. Machine Learning 1: 363–366, 1986. Kluwer Academic Publishers, Boston. 1986. (with Brian C. Falkenhainer) Integrating quantitative and qualitative discovery: The ABACUS system. Machine Learning: Volume 1, Issue 4, pp 367–401.

References

External links Obituary Ryszard S. Michalski (1937–2007), by Adam Borkowski, 2007

Worked examples

Example 1 — a first encounter with Ryszard S. Michalski

Start with the simplest possible case. Write down what Ryszard S. Michalski claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In astronomy, 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 Ryszard S. Michalski 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 Ryszard S. Michalski 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 Ryszard S. Michalski

In research: Ryszard S. Michalski appears in astronomy 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 Ryszard S. Michalski 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: Ryszard S. Michalski is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1937 births, 2007 deaths, American computer scientists, so understanding it makes those chapters shorter.
In everyday life: Look for Ryszard S. Michalski 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 Ryszard S. Michalski in 20 minutes

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

Frequently asked questions

What is Ryszard S. Michalski in simple terms?

Why does Ryszard S. Michalski matter?

Because it connects several astronomy 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 Ryszard S. Michalski?

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 Ryszard S. Michalski.