astronomy

Moshe Tennenholtz

Moshe Tennenholtz 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 Moshe Tennenholtz rather than just read about it. In short: Moshe Tennenholtz (Hebrew: משה טננהולץ) is an Israeli computer scientist and professor with the faculty of Data and Decision Sciences at the Technion – Israel Institute of Technology, where he holds the Sondheimer Technion Academic Chair. Biography Tennenholtz received his B.Sc. in mathematics from Tel Aviv University in 1986, and his M.Sc. and Ph.D. in 1987 and 1991 respectively from the Department of Applied Mathe…

Key takeaways

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

Reference excerpt

Moshe Tennenholtz (Hebrew: משה טננהולץ) is an Israeli computer scientist and professor with the faculty of Data and Decision Sciences at the Technion – Israel Institute of Technology, where he holds the Sondheimer Technion Academic Chair.

Biography Tennenholtz received his B.Sc. in mathematics from Tel Aviv University in 1986, and his M.Sc. and Ph.D. in 1987 and 1991 respectively from the Department of Applied Mathematics and Computer Science in the Weizmann Institute. From 1991 to 1993 he worked in the Robotics Laboratory at Stanford University, after which he joined the faculty at the Technion in Haifa. He returned to Stanford briefly as a visiting professor from 1999 to 2002 before returning to the Technion. In 2008 he started working at Microsoft Research and in 2011 he founded the basic research group at the Microsoft Israel R&D center. He has served as editor-in-chief of the Journal of Artificial Intelligence Research, associate editor of Games and Economic Behavior, the international journal of Autonomous Agents and Multi-Agent Systems, served on the editorial board of the Journal of Machine Learning Research, and served on the editorial board of AI Magazine. He served as program chair of the ACM Electronic Commerce conference and of the TARK conference.

Recognition He is an AAAI Fellow, an ACM fellow, and a fellow of the Society for the Advancement of Economic Theory. He is a winner of the Allen Newell award and of the John McCarthy award for pioneering contributions to the interplay between artificial intelligence and game theory. He also received the ACM SIGART Autonomous Agents Research Award for 2012. He was elected as an ACM Fellow in 2019 "for contributions to AI and algorithmic game theory".

References

Worked examples

Example 1 — a first encounter with Moshe Tennenholtz

Start with the simplest possible case. Write down what Moshe Tennenholtz 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 Moshe Tennenholtz 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 Moshe Tennenholtz 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 Moshe Tennenholtz

In research: Moshe Tennenholtz 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 Moshe Tennenholtz 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: Moshe Tennenholtz is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1960 births, Academic staff of Technion – Israel Institute of Technology, Artificial intelligence researchers, so understanding it makes those chapters shorter.
In everyday life: Look for Moshe Tennenholtz 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 Moshe Tennenholtz in 20 minutes

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

Frequently asked questions

What is Moshe Tennenholtz in simple terms?

Why does Moshe Tennenholtz 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 Moshe Tennenholtz?

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 Moshe Tennenholtz.