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Robertson–Webb envy-free cake-cutting algorithm

Robertson–Webb envy-free cake-cutting algorithm 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 Robertson–Webb envy-free cake-cutting algorithm rather than just read about it. In short: The Robertson–Webb protocol is a protocol for envy-free cake-cutting which is also near-exact. It has the following properties: It works for any number (n) of partners.

Key takeaways

  • Robertson–Webb envy-free cake-cutting algorithm 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 Robertson–Webb envy-free cake-cutting algorithm to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Robertson–Webb envy-free cake-cutting algorithm from memory before moving on to harder problems.

Reference excerpt

The Robertson–Webb protocol is a protocol for envy-free cake-cutting which is also near-exact. It has the following properties:

It works for any number (n) of partners. It works for any set of weights representing different entitlements of the partners. The pieces are not necessarily connected, i.e. each partner might receive a collection of small "crumbs". The number of queries is finite but unbounded – it is not known in advance how many queries will be needed. The protocol was developed by Jack M. Robertson and William A. Webb. It was first published in 1997 and later in 1998.

Problem definition A cake C has to be divided among n agents. Each agent i has:

A value-measure Vi on subsets of C; A weight wi representing the fraction of C to which the agent is entitled. The sum of all wi is 1. If all agents have the same rights, then wi = 1/n for all i, but in general the weights may be different.

It is required to partition C into n subsets, not necessarily connected, such that, for every two agents i and h: V i ( X i ) / w i ≥ V i ( X h ) / w h {\displaystyle V_{i}(X_{i})/w_{i}\geq V_{i}(X_{h})/w_{h}} So i does not envy j when taking their different entitlements into account.

Details The main difficulty in designing an envy-free procedure for n > 2 agents is that the problem is not "divisible". I.e., if we divide half of the cake among n/2 agents in an envy-free manner, we cannot just let the other n/2 agents divide the other half in the same manner, because this might cause the first group of n/2 agents to be envious (e.g., it is possible that A and B both believe they got 1/2 of their half which is 1/4 of the entire cake; C and D also believe the same way; but, A believes that C actually got the entire half while D got nothing, so A envies C). The Robertson–Webb protocol addresses this difficulty by requiring that the division is not only envy-free but also near-exact. The recursive part of the protocol is the following subroutine.

Inputs Any piece of cake X; Any ε > 0; n players, A1, …, An; m ≤ n players which are identified as "active players", A1, …, Am (the other n − m players are identified as "watching players"); Any set of m positive weights w1, …, wm;

Output A partition of X to pieces X1, …, Xm, assigned to the m active players, such that:

For every active player i and every other player h (active or watching): V i ( X i ) / w i ≥ V i ( X h ) / w h {\displaystyle V_{i}(X_{i})/w_{i}\geq V_{i}(X_{h})/w_{h}} So agent i does not envy agent h when taking their different entitlements into account. The division is ε-near-exact with the given weights among all n players – both active and watching.

Procedure Note: the presentation here is informal and simplified. A more accurate presentation is given in the book. Use a near-exact division procedure on X and get a partition which all n players view as ε-near-exact with weights w1, …, wm. Let one of the active players (e.g. A1) cut the pieces such that the division is exact for him, i.e. for every j: V1(Xj)/V1(X) = wj. If all other active players agree with the cutter, then just give piece Xi to active player Ai. This division is envy-free among the active players, so we are done. Otherwise, there is some piece P on which there is disagreement among the active players. By cutting P to smaller pieces if necessary, we may bound the disagreement such that all players agree that: V(P)/V(X) < ε. Split the active players to two camps: the "optimists" who think that P is more valuable, and the "pessimists" who think that P is less valuable. Let δ be the difference between the values, such that for every optimist i and every pessimist j: Vi(P)/Vi(X) – Vj(P)/Vj(X) > δ. Divide the remaining cake, X − P, into pieces Q and R, such that the division is near-exact among all n players. Assign P ∪ Q to the optimists. Because they believe that P is valuable, they necessarily believe that P ∪ Q is sufficiently valuable to more than cover their due share. Assign R to the pessimists. Because they believe that P is less valuable, they necessarily believe that the remainder, R, is sufficiently valuable to more than cover their due share. At this point we have partitioned the active players to two camps, each collectively claiming complementary portions of the cake and each camp is more than satisfied with their collective portion. It remains to divide each portion of the cake to the players in its camp. This is done by two recursive applications of the procedure:

Recursively partition P ∪ Q among the optimists (i.e. the optimists are active and all other players are only watching). Recursively partition R among the pessimists. In both applications, the near-exactness factor should be at most δ. Because the resulting partition is δ-near-exact among all n players, the partition among the optimists doesn't cause envy among the pessimists and vice versa. Thus the over-all division is both envy-free and near-exact.

See also Brams–Taylor protocol – another envy-free protocol with disconnected pieces and finite unbounded runtime. Does not guarantee near-exactness. Simmons–Su protocols – envy-free protocol which guarantees connected pieces but the runtime might be infinite. Does not guarantee near-exactness. Robertson–Webb query model

References

Worked examples

Example 1 — a first encounter with Robertson–Webb envy-free cake-cutting algorithm

Start with the simplest possible case. Write down what Robertson–Webb envy-free cake-cutting algorithm 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 Robertson–Webb envy-free cake-cutting algorithm 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 Robertson–Webb envy-free cake-cutting algorithm 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 Robertson–Webb envy-free cake-cutting algorithm

In research
Robertson–Webb envy-free cake-cutting algorithm 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 Robertson–Webb envy-free cake-cutting algorithm 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
Robertson–Webb envy-free cake-cutting algorithm is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cake-cutting, Fair division protocols, so understanding it makes those chapters shorter.
In everyday life
Look for Robertson–Webb envy-free cake-cutting algorithm 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 Robertson–Webb envy-free cake-cutting algorithm in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Robertson–Webb envy-free cake-cutting algorithm means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Robertson–Webb envy-free cake-cutting algorithm out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Robertson–Webb envy-free cake-cutting algorithm in simple terms?

The Robertson–Webb protocol is a protocol for envy-free cake-cutting which is also near-exact. It has the following properties: It works for any number (n) of partners.

Why does Robertson–Webb envy-free cake-cutting algorithm 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 Robertson–Webb envy-free cake-cutting algorithm?

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 Robertson–Webb envy-free cake-cutting algorithm.

Tags

  • Cake-cutting
  • Fair division protocols

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