Truthful cake-cutting

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Truthful cake-cutting is the study of algorithms for fair cake-cutting that are also truthful mechanisms, i.e., they incentivize the participants to reveal their true valuations to the various parts of the cake.

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The classic divide and choose procedure for cake-cutting is not truthful: if the cutter knows the chooser's preferences, they can get much more than 1/2 by acting strategically. For example, suppose the cutter values a piece by its size while the chooser values a piece by the amount of chocolate in it. So the cutter can cut the cake into two pieces with almost the same amount of chocolate, such that the smaller piece has slightly more chocolate. Then, the chooser will take the smaller piece and the cutter will win the larger piece, which may be worth much more than 1/2 (depending on how the chocolate is distributed).

Randomized mechanisms

There is a trivial randomized truthful mechanism for fair cake-cutting: select a single agent uniformly at random, and give him/her the entire cake. This mechanism is trivially truthful because it asks no questions. Moreover, it is fair in expectation: the expected value of each partner is exactly 1/n. However, the resulting allocation is not fair. The challenge is to develop truthful mechanisms that are fair ex-post and not just ex-ante. Several such mechanisms have been developed.

Exact division mechanism

An exact division (aka consensus division) is a partition of the cake into n pieces such that each agent values each piece at exactly 1/n. The existence of such a division is a corollary of the Dubins–Spanier convexity theorem. Moreover, there exists such a division with at most cuts; this is a corollary of the Stromquist–Woodall theorem and the necklace splitting theorem.

In general, an exact division cannot be found by a finite algorithm. However, it can be found in some special cases, for example when all agents have piecewise-linear valuations. Suppose we have a non-truthful algorithm (or oracle) for finding an exact division. It can be used to construct a randomized mechanism that is truthful in expectation. [1] [2] The randomized mechanism is a direct-revelation mechanism - it starts by asking all agents to reveal their entire value-measures:

  1. Ask the agents to report their value measures.
  2. Use the existing algorithm/oracle to generate an exact division.
  3. Perform a random permutation on the consensus partition and give each partner one of the pieces.

Here, the expected value of each agent is always 1/n regardless of the reported value function. Hence, the mechanism is truthful – no agent can gain anything from lying. Moreover, a truthful partner is guaranteed a value of exactly 1/n with probability 1 (not only in expectation). Hence the partners have an incentive to reveal their true value functions.

Super-proportional mechanism

A super-proportional division is a cake-division in which each agent receives strictly more than 1/n by their own value measures. Such a division is known to exist if and only if there are at least two agents that have different valuations to at least one piece of the cake. Any deterministic mechanism that always returns a proportional division, and always returns a super-proportional division when it exists, cannot be truthful.

Mossel and Tamuz present a super-proportional randomized mechanism that is truthful in expectation: [1]

  1. Pick a division from a certain distribution D over divisions.
  2. Ask each agent to evaluate his/her piece.
  3. If all n evaluations are more than 1/n, then implement the allocation and finish.
  4. Otherwise, use the exact-division mechanism.

The distribution D in step 1 should be chosen such that, regardless of the agents' valuations, there is a positive probability that a super-proportional division be selected iff it exists. Then, in step 2 it is optimal for each agent to report the true value: reporting a lower value either has no effect or might cause the agent's value to drop from super-proportional to just proportional (in step 4); reporting a higher value either has no effect or might cause the agent's value to drop from proportional to less than 1/n (in step 3).

Approximate exact division using queries

Suppose that, rather than directly revealing their valuations, the agents reveal their values indirectly by answering mark and eval queries (as in the Robertson-Webb model).

Branzei and Miltersen [3] show that the exact-division mechanism can be "discretized" and executed in the query model. This yields, for any , a randomized query-based protocol, that asks at most queries, is truthful in expectation, and allocates each agent a piece of value between and , by the valuations of all agents.

On the other hand, they prove that, in any deterministic truthful query-based protocol, if all agents value all parts of the cake positively, there is at least one agent who gets the empty piece. This implies that, if there are only two agents, then at least one agent is a "dictator" and gets the entire cake. Obviously, any such mechanism cannot be envy-free.

Randomized mechanism for piecewise-constant valuations

Suppose all agents have piecewise-constant valuations. This means that, for each agent, the cake is partitioned into finitely many subsets, and the agent's value density in each subset is constant. For this case, Aziz and Ye present a randomized algorithm that is more economically-efficient: Constrained Serial Dictatorship is truthful in expectation, robust proportional, and satisfies a property called unanimity: if each agent's most preferred 1/n length of the cake is disjoint from other agents, then each agent gets their most preferred 1/n length of the cake. This is a weak form of efficiency that is not satisfied by the mechanisms based on exact division. When there are only two agents, it is also polynomial-time and robust envy-free. [4]

Deterministic mechanisms: piecewise-constant valuations

For deterministic mechanisms, the results are mostly negative, even when all agents have piecewise-constant valuations.

Kurokawa, Lai and Procaccia prove that there is no deterministic, truthful and envy-free mechanism that requires a bounded number of Robertson-Webb queries. [5]

Aziz and Ye prove that there is no deterministic truthful mechanism that satisfies either one of the following properties: [4]

Menon and Larson introduce the notion of ε-truthfulness, which means that no agent gains more than a fraction ε from misreporting, where ε is a positive constant independent of the agents' valuations. They prove that no deterministic mechanism satisfies either one of the following properties: [6]

They present a minor modification to the Even–Paz protocol and prove that it is ε-truthful with ε = 1 - 3/(2n) when n is even, and ε = 1 - 3/(2n) + 1/n2 when n is odd.

Bei, Chen, Huzhang, Tao and Wu prove that there is no deterministic, truthful and envy-free mechanism, even in the direct-revelation model, that satisfies either one of the following additional properties: [7]

Note that these impossibility results hold with or without free disposal.

On the positive side, in a replicate economy, where each agent is replicated k times, there are envy-free mechanisms in which truth-telling is a Nash equilibrium: [7]

Tao improves the previous impossibility result by Bei, Chen, Huzhang, Tao and Wu and shows that there is no deterministic, truthful and proportional mechanism, even in the direct-revelation model, and even when all of the followings hold: [8]

It is open whether this impossibility result extends to three or more agents.

On the positive side, Tao presents two algorithms that attain a weaker notion called "proportional risk-averse truthfulness" (PRAT). It means that, in any profitable deviation for agent i, there exist valuations of the other agents, for which i gets less than his proportional share. This property is stronger than "risk-averse truthfulness", which means that, in any profitable deviation for i, there exist valuations of the other agents, for which i gets less than his value in a truthful reporting. He presents an algorithm that is PRAT and envy-free, and an algorithm that is PRAT, proportional and connected. [8]

Piecewise-uniform valuations

Suppose all agents have piecewise-uniform valuations. This means that, for each agent, there is a subset of the cake that is desirable for the agent, and the agent's value for each piece is just the amount of desirable cake that it contains. For example, suppose some parts of the cake are covered by a uniform layer of chocolate, while other parts are not. An agent who values each piece only by the amount of chocolate it contains has a piecewise-uniform valuation. This is a special case of piecewise-constant valuations. Several truthful algorithms have been developed for this special case.

Chen, Lai, Parkes and Procaccia present a direct-revelation mechanism that is deterministic, proportional, envy-free, Pareto-optimal, and polynomial-time. [2] It works for any number of agents. Here is an illustration of the CLPP mechanism for two agents (where the cake is an interval).

  1. Ask each agent to report his/her desired intervals.
  2. Each sub-interval, that is desired by no agent, is discarded.
  3. Each sub-interval, that is desired by exactly one agent, is allocated to that agent.
  4. The sub-intervals, that are desired by both agents, are allocated such that both agents get an equal total length.

Now, if an agent says that he wants an interval that he actually does not want, then he may get more useless cake in step 3 and less useful cake in step 4. If he says that he does not want an interval that he actually wants, then he gets less useful cake in step 3 and more useful cake in step 4, however, the amount given in step 4 is shared with the other agent, so all in all, the lying agent is at a loss. The mechanism can be generalized to any number of agents.

The CLPP mechanism relies on the free disposal assumption, i.e., the ability to discard pieces that are not desired by any agent.

Note: Aziz and Ye [4] presented two mechanisms that extend the CLPP mechanism to piecewise-constant valuations - Constrained Cake Eating Algorithm and Market Equilibrium Algorithm. However, both these extensions are no longer truthful when the valuations are not piecewise-uniform.

Maya and Nisan show that the CLPP mechanism is unique in the following sense. [9] Consider the special case of two agents with piecewise-uniform valuations, where the cake is [0,1], Alice wants only the subinterval [0,a] for some a<1, and Bob desires only the subinterval [1-b,1] for some b<1. Consider only non-wasteful mechanisms - mechanisms that allocate each piece desired by at least one player to a player who wants it. Each such mechanism must give Alice a subset [0,c] for some c<1 and Bob a subset [1-d,1] for some d<1. In this model:

They also show that, even for 2 agents, any truthful mechanism achieves at most 0.93 of the optimal social welfare.

Li, Zhang and Zhang show that the CLPP mechanism works well even when there are externalities (i.e., some agents derive some benefit from the value given to others), as long as the externalities are sufficiently small. On the other hand, if the externalities (either positive or negative) are large, no truthful non-wasteful and position independent mechanism exists. [10]

Alijani, Farhadi, Ghodsi, Seddighin and Tajik present several mechanisms for special cases of piecewise-uniform valuations: [11]

Bei, Huzhang and Suksompong present a mechanism for two agents with piecewise-uniform valuations, that has the same properties of CLPP (truthful, deterministic, proportional, envy-free, Pareto-optimal and runs in polynomial time), but guarantees that the entire cake is allocated: [12]

  1. Find the smallest x in [0,1] such that Alice's desired length in [0,x] equals Bob's desired length in [x,1].
  2. Give Alice the intervals in [0,x] valued by Alice and the intervals in [x,1] not valued by Bob; give the remainder to Bob.

The BHS mechanism works both for cake-cutting and for chore division (where the agents' valuations are negative). Note that BHS does not satisfy some natural desirable properties:

This is not a problem with the specific mechanism: it is provably impossible to have a truthful and envy-free mechanism that allocates the entire cake and guarantees any of these three properties, even for two agents with piecewise-uniform valuations. [12]

The BHS mechanism was extended to any number of agents, but only for a special case of piecewise-uniform valuations, in which each agent desires only a single interval of the form [0, xi].

Ianovsky [13] proves that no truthful mechanism can attain a utilitarian-optimal cake-cutting, even when all agents have piecewise-uniform valuations. Moreover, no truthful mechanism can attain an allocation with utilitarian welfare at least as large as any other mechanism. However, there is a simple truthful mechanism (denoted Lex Order) that is non-wasteful: give to agent 1 all pieces that he likes; then, give to agent 2 all pieces that he likes and were not yet given to agent 1; etc. A variant of this mechanism is the Length Game, in which the agents are renamed by the total length of their desired intervals, such that the agent with the shortest interval is called 1, the agent with the next-shortest interval is called 2, etc. This is not a truthful mechanism, however:

Summary of truthful mechanisms and impossibility results

NameTypeDeterministic?#agents(n)Valuations [14] Chores? [15] Run timeAll? [16] PO? [17] EF? [18] Anon? [19] Conn? [20] Pos.Ob.? [21] No Waste? [22]
Exact division [1] [2] DirectNoManyGeneralYesUnbounded [23] YesNoYesYesNo ??
Super-proportional [1] DirectNoManyGeneralYesUnboundedYesNoNoYesNo ??
Discrete exact division [3] QueriesNoManyGeneralYesYesNo-EFYesNo??
Constrained Serial Dictatorship [4] DirectNoManyPWC??NoUnanimityProp.?No??
CLPP [2] DirectYesManyPWUNoPolynomialNoYesYesYesNo ?Yes
BHS 1, 2DirectYes2PWUYesPolynomialYesYesYesNoNoNoYes
BHS 3, 4DirectYesManyPWU1YesPolynomialYesYesYes (for cakes)???Yes
Expansion [11] DirectYesManyPWU1+order?Polynomial??Yes?Yes??
Expansion+ UnlockingDirectYesManyPWU1?Polynomial??Yes?2n-2 cuts??
IMPOSSIBLE COMBINATIONS:
[BM] [3] QueriesYes2+Any
[BHS] [12] DirectYes2+PWUYesYesYes
[BHS]DirectYes2+PWUYesYesYes
[BHS]DirectYes2+PWUYesYesYes
[T] [8] DirectYes2+PWCYes(even for Prop.)
[BCHTW] [7] DirectYes2+PWCYesYesYes
[BCHTW]DirectYes2+PWCYesYesYes
[BCHTW]DirectYes2+PWCYesYesYes
[BCHTW]SequentialYes2+PWCYesYes


See also

Related Research Articles

Fair division is the problem in game theory of dividing a set of resources among several people who have an entitlement to them so that each person receives their due share. That problem arises in various real-world settings such as division of inheritance, partnership dissolutions, divorce settlements, electronic frequency allocation, airport traffic management, and exploitation of Earth observation satellites. It is an active research area in mathematics, economics, dispute resolution, etc. The central tenet of fair division is that such a division should be performed by the players themselves, maybe using a mediator but certainly not an arbiter as only the players really know how they value the goods.

An envy-free cake-cutting is a kind of fair cake-cutting. It is a division of a heterogeneous resource ("cake") that satisfies the envy-free criterion, namely, that every partner feels that their allocated share is at least as good as any other share, according to their own subjective valuation.

A proportional division is a kind of fair division in which a resource is divided among n partners with subjective valuations, giving each partner at least 1/n of the resource by his/her own subjective valuation.

Exact division, also called consensus division, is a partition of a continuous resource ("cake") into some k pieces, such that each of n people with different tastes agree on the value of each of the pieces. For example, consider a cake which is half chocolate and half vanilla. Alice values only the chocolate and George values only the vanilla. The cake is divided into three pieces: one piece contains 20% of the chocolate and 20% of the vanilla, the second contains 50% of the chocolate and 50% of the vanilla, and the third contains the rest of the cake. This is an exact division (with k = 3 and n = 2), as both Alice and George value the three pieces as 20%, 50% and 30% respectively. Several common variants and special cases are known by different terms:

<span class="mw-page-title-main">Fair cake-cutting</span> Fair division problem

Fair cake-cutting is a kind of fair division problem. The problem involves a heterogeneous resource, such as a cake with different toppings, that is assumed to be divisible – it is possible to cut arbitrarily small pieces of it without destroying their value. The resource has to be divided among several partners who have different preferences over different parts of the cake, i.e., some people prefer the chocolate toppings, some prefer the cherries, some just want as large a piece as possible. The division should be unanimously fair – each person should receive a piece believed to be a fair share.

The last diminisher procedure is a procedure for fair cake-cutting. It involves a certain heterogenous and divisible resource, such as a birthday cake, and n partners with different preferences over different parts of the cake. It allows the n people to achieve a proportional division, i.e., divide the cake among them such that each person receives a piece with a value of at least 1/n of the total value according to his own subjective valuation. For example, if Alice values the entire cake as $100 and there are 5 partners then Alice can receive a piece that she values as at least $20, regardless of what the other partners think or do.

Efficient cake-cutting is a problem in economics and computer science. It involves a heterogeneous resource, such as a cake with different toppings or a land with different coverings, that is assumed to be divisible - it is possible to cut arbitrarily small pieces of it without destroying their value. The resource has to be divided among several partners who have different preferences over different parts of the cake, i.e., some people prefer the chocolate toppings, some prefer the cherries, some just want as large a piece as possible, etc. The allocation should be economically efficient. Several notions of efficiency have been studied:

The fair pie-cutting problem is a variation of the fair cake-cutting problem, in which the resource to be divided is circular.

Equitable (EQ) cake-cutting is a kind of a fair cake-cutting problem, in which the fairness criterion is equitability. It is a cake-allocation in which the subjective value of all partners is the same, i.e., each partner is equally happy with his/her share. Mathematically, that means that for all partners i and j:

A proportional cake-cutting is a kind of fair cake-cutting. It is a division of a heterogeneous resource ("cake") that satisfies the proportionality criterion, namely, that every partner feels that his allocated share is worth at least 1/n of the total.

Weller's theorem is a theorem in economics. It says that a heterogeneous resource ("cake") can be divided among n partners with different valuations in a way that is both Pareto-efficient (PE) and envy-free (EF). Thus, it is possible to divide a cake fairly without compromising on economic efficiency.

Utilitarian cake-cutting is a rule for dividing a heterogeneous resource, such as a cake or a land-estate, among several partners with different cardinal utility functions, such that the sum of the utilities of the partners is as large as possible. It is a special case of the utilitarian social choice rule. Utilitarian cake-cutting is often not "fair"; hence, utilitarianism is often in conflict with fair cake-cutting.

A simultaneous eating algorithm(SE) is an algorithm for allocating divisible objects among agents with ordinal preferences. "Ordinal preferences" means that each agent can rank the items from best to worst, but cannot (or does not want to) specify a numeric value for each item. The SE allocation satisfies SD-efficiency - a weak ordinal variant of Pareto-efficiency (it means that the allocation is Pareto-efficient for at least one vector of additive utility functions consistent with the agents' item rankings).

Symmetric fair cake-cutting is a variant of the fair cake-cutting problem, in which fairness is applied not only to the final outcome, but also to the assignment of roles in the division procedure.

Truthful resource allocation is the problem of allocating resources among agents with different valuations over the resources, such that agents are incentivized to reveal their true valuations over the resources.

In computer science, the Robertson–Webb (RW) query model is a model of computation used by algorithms for the problem of fair cake-cutting. In this problem, there is a resource called a "cake", and several agents with different value measures on the cake. The goal is to divide the cake among the agents such that each agent will consider his/her piece as "fair" by his/her personal value measure. Since the agents' valuations can be very complex, they cannot - in general - be given as inputs to a fair division algorithm. The RW model specifies two kinds of queries that a fair division algorithm may ask the agents: Eval and Cut. Informally, an Eval query asks an agent to specify his/her value to a given piece of the cake, and a Cut query asks an agent to specify a piece of cake with a given value.

Online fair division is a class of fair division problems in which the resources, or the people to whom they should be allocated, or both, are not all available when the allocation decision is made. Some situations in which not all resources are available include:

Fair division among groups is a class of fair division problems, in which the resources are allocated among groups of agents, rather than among individual agents. After the division, all members in each group consume the same share, but they may have different preferences; therefore, different members in the same group might disagree on whether the allocation is fair or not. Some examples of group fair division settings are:

A piecewise-constant valuation is a kind of a function that represents the utility of an agent over a continuous resource, such as land. It occurs when the resource can be partitioned into a finite number of regions, and in each region, the value-density of the agent is constant. A piecewise-uniform valuation is a piecewise-constant valuation in which the constant is the same in all regions.

References

  1. 1 2 3 4 Mossel, Elchanan; Tamuz, Omer (2010). Truthful Fair Division. Lecture Notes in Computer Science. Vol. 6386. Springer Berlin Heidelberg. pp. 288–299. arXiv: 1003.5480 . Bibcode:2010LNCS.6386..288M. doi:10.1007/978-3-642-16170-4_25. ISBN   9783642161704. S2CID   11732339.{{cite book}}: |journal= ignored (help)
  2. 1 2 3 4 Chen, Yiling; Lai, John K.; Parkes, David C.; Procaccia, Ariel D. (2013-01-01). "Truth, justice, and cake cutting" (PDF). Games and Economic Behavior. 77 (1): 284–297. doi:10.1016/j.geb.2012.10.009. ISSN   0899-8256. S2CID   2096977.
  3. 1 2 3 Brânzei, Simina; Miltersen, Peter Bro (2015-06-22). "A Dictatorship Theorem for Cake Cutting". Twenty-Fourth International Joint Conference on Artificial Intelligence.
  4. 1 2 3 4 Aziz, Haris; Ye, Chun (2014). Liu, Tie-Yan; Qi, Qi; Ye, Yinyu (eds.). Cake Cutting Algorithms for Piecewise Constant and Piecewise Uniform Valuations. Lecture Notes in Computer Science. Vol. 8877. Springer International Publishing. pp. 1–14. doi:10.1007/978-3-319-13129-0_1. ISBN   9783319131290. S2CID   18365892.{{cite book}}: |journal= ignored (help)
  5. Kurokawa, David; Lai, John K.; Procaccia, Ariel D. (2013-06-30). "How to Cut a Cake Before the Party Ends". Twenty-Seventh AAAI Conference on Artificial Intelligence. 27: 555–561. doi: 10.1609/aaai.v27i1.8629 . S2CID   12638556.
  6. Menon, Vijay; Larson, Kate (2017-05-17). "Deterministic, Strategyproof, and Fair Cake Cutting". arXiv: 1705.06306 [cs.GT].
  7. 1 2 3 Bei, Xiaohui; Chen, Ning; Huzhang, Guangda; Tao, Biaoshuai; Wu, Jiajun (2017). "Cake Cutting: Envy and Truth". Proceedings of the 26th International Joint Conference on Artificial Intelligence. IJCAI'17. AAAI Press: 3625–3631. ISBN   9780999241103.
  8. 1 2 3 Tao, Biaoshuai (2022-07-13). "On Existence of Truthful Fair Cake Cutting Mechanisms". Proceedings of the 23rd ACM Conference on Economics and Computation. pp. 404–434. arXiv: 2104.07387 . doi:10.1145/3490486.3538321. ISBN   9781450391504. S2CID   233241229.
  9. Maya, Avishay; Nisan, Noam (2012). Goldberg, Paul W. (ed.). Incentive Compatible Two Player Cake Cutting. Lecture Notes in Computer Science. Vol. 7695. Springer Berlin Heidelberg. pp. 170–183. arXiv: 1210.0155 . Bibcode:2012arXiv1210.0155M. doi:10.1007/978-3-642-35311-6_13. ISBN   9783642353116. S2CID   1927798.{{cite book}}: |journal= ignored (help)
  10. Li, Minming; Zhang, Jialin; Zhang, Qiang (2015-06-22). "Truthful Cake Cutting Mechanisms with Externalities: Do Not Make Them Care for Others Too Much!". Twenty-Fourth International Joint Conference on Artificial Intelligence.
  11. 1 2 Alijani, Reza; Farhadi, Majid; Ghodsi, Mohammad; Seddighin, Masoud; Tajik, Ahmad S. (2017-02-10). "Envy-Free Mechanisms with Minimum Number of Cuts". Thirty-First AAAI Conference on Artificial Intelligence. 31. doi: 10.1609/aaai.v31i1.10584 . S2CID   789550.
  12. 1 2 3 Bei, Xiaohui; Huzhang, Guangda; Suksompong, Warut (2020). "Truthful fair division without free disposal". Social Choice and Welfare. 55 (3): 523–545. arXiv: 1804.06923 . doi:10.1007/s00355-020-01256-0. PMC   7497335 . PMID   33005068.
  13. Ianovski, Egor (2012-03-01). "Cake Cutting Mechanisms". arXiv: 1203.0100 [cs.GT].
  14. PWC = piecewise-constant, PWU = piecewise-uniform, PWU1 = piecewise-uniform with a single desired interval.
  15. Whether the algorithm can handle also cakes with negative utilities (chores).
  16. Whether the entire cake is divided, with no disposal.
  17. Whether the resulting allocation is always Pareto optimal.
  18. Whether the resulting allocation is always envy-free.
  19. Whether the mechanismn is anonymous.
  20. Whether the resulting pieces are always connected.
  21. Whether the mechanism is position oblivious.
  22. Whether the algorithm guarantees non-wastefulness.
  23. The run-time is dominated by calculating an exact division. In general it is unbounded, but in special cases it may be polynomial.