Fair division

Last updated

Fair division is the problem of dividing a set of resources among several people who have an entitlement to them, such that each person receives their due share. This 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. This is an active research area in mathematics, economics (especially social choice theory), game theory, dispute resolution, and more. 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.

Contents

The archetypal fair division algorithm is divide and choose. It demonstrates that two agents with different tastes can divide a cake such that each of them believes that he got the best piece. The research in fair division can be seen as an extension of this procedure to various more complex settings.

There are many different kinds of fair division problems, depending on the nature of goods to divide, the criteria for fairness, the nature of the players and their preferences, and other criteria for evaluating the quality of the division.

Things that can be divided

Formally, a fair division problem is defined by a set and a group of players. A division is a partition of into disjoint subsets: , one subset per player.

The set can be of various types:

Additionally, the set to be divided may be:

Finally, it is common to make some assumptions about whether the items to be divided are:

Based on these distinctions, several general types of fair division problems have been studied:

Combinations and special cases are also common:

Definitions of fairness

Most of what is normally called a fair division is not considered so by the theory because of the use of arbitration. This kind of situation happens quite often with mathematical theories named after real life problems. The decisions in the Talmud on entitlement when an estate is bankrupt reflect some quite complex ideas about fairness, [1] and most people would consider them fair. However they are the result of legal debates by rabbis rather than divisions according to the valuations of the claimants.

According to the Subjective theory of value, there cannot be an objective measure of the value of each item. Therefore, objective fairness is not possible, as different people may assign different values to each item. Empirical experiments on how people define the concept of fairness [2] lead to inconclusive results.

Therefore, most current research on fairness focuses on concepts of subjective fairness. Each of the people is assumed to have a personal, subjective utility function or value function, , which assigns a numerical value to each subset of . Often the functions are assumed to be normalized, so that every person values the empty set as 0 ( for all i), and the entire set of items as 1 ( for all i) if the items are desirable, and -1 if the items are undesirable. Examples are:

Based on these subjective value functions, there are a number of widely used criteria for a fair division. Some of these conflict with each other but often they can be combined. The criteria described here are only for when each player is entitled to the same amount:

All the above criteria assume that the participants have equal entitlements. If different participants have different entitlements (e.g., in a partnership where each partner invested a different amount), then the fairness criteria should be adapted accordingly. See Proportional cake-cutting with different entitlements.

Additional requirements

In addition to fairness, it is sometimes desired that the division be Pareto optimal, i.e., no other allocation would make someone better off without making someone else worse off. The term efficiency comes from the economics idea of the efficient market. A division where one player gets everything is optimal by this definition so on its own this does not guarantee even a fair share. See also efficient cake-cutting and the price of fairness.

Berlin divided by the Potsdam Conference Berlin Blockade-map.svg
Berlin divided by the Potsdam Conference

In the real world people sometimes have a very accurate idea of how the other players value the goods and they may care very much about it. The case where they have complete knowledge of each other's valuations can be modeled by game theory. Partial knowledge is very hard to model. A major part of the practical side of fair division is the devising and study of procedures that work well despite such partial knowledge or small mistakes.

An additional requirement is that the fair division procedure be a truthful mechanism, i.e., it should be a dominant strategy for the participants to report their true valuations. This requirement is usually very hard to satisfy in combination with fairness and Pareto-efficiency.

A generalization of the problem is to allow each interested party to consist of several players who share the same set of resources but have different preferences. [3] [4]

Procedures

A fair division procedure lists actions to be performed by the players in terms of the visible data and their valuations. A valid procedure is one that guarantees a fair division for every player who acts rationally according to their valuation. Where an action depends on a player's valuation the procedure is describing the strategy a rational player will follow. A player may act as if a piece had a different value but must be consistent. For instance if a procedure says the first player cuts the cake in two equal parts then the second player chooses a piece, then the first player cannot claim that the second player got more.

What the players do is:

It is assumed the aim of each player is to maximize the minimum amount they might get, or in other words, to achieve the maximin.

Procedures can be divided into discrete vs. continuous procedures. A discrete procedure would for instance only involve one person at a time cutting or marking a cake. Continuous procedures involve things like one player moving a knife and the other saying "stop". Another type of continuous procedure involves a person assigning a value to every part of the cake.

For a list of fair division procedures, see Category:Fair division protocols.

History

According to Sol Garfunkel, the cake-cutting problem had been one of the most important open problems in 20th century mathematics, [5] when the most important variant of the problem was finally solved with the Brams-Taylor procedure by Steven Brams and Alan Taylor in 1995.

Divide and choose's origins are undocumented. The related activities of bargaining and barter are also ancient. Negotiations involving more than two people are also quite common, the Potsdam Conference is a notable recent example.

The theory of fair division dates back only to the end of the second world war. It was devised by a group of Polish mathematicians, Hugo Steinhaus, Bronisław Knaster and Stefan Banach, who used to meet in the Scottish Café in Lvov (then in Poland). A proportional (fair division) division for any number of players called 'last-diminisher' was devised in 1944. This was attributed to Banach and Knaster by Steinhaus when he made the problem public for the first time at a meeting of the Econometric Society in Washington D.C. on 17 September 1947. At that meeting he also proposed the problem of finding the smallest number of cuts necessary for such divisions.

For the history of envy-free cake-cutting, see envy-free cake-cutting.

See also

Related Research Articles

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.

Chore division is a fair division problem in which the divided resource is undesirable, so that each participant wants to get as little as possible. It is the mirror-image of the fair cake-cutting problem, in which the divided resource is desirable so that each participant wants to get as much as possible. Both problems have heterogeneous resources, meaning that the resources are nonuniform. In cake division, cakes can have edge, corner, and middle pieces along with different amounts of frosting. Whereas in chore division, there are different chore types and different amounts of time needed to finish each chore. Similarly, both problems assume that the resources are divisible. Chores can be infinitely divisible, because the finite set of chores can be partitioned by chore or by time. For example, a load of laundry could be partitioned by the number of articles of clothing and/or by the amount of time spent loading the machine. The problems differ, however, in the desirability of the resources. The chore division problem was introduced by Martin Gardner in 1978.

An exact division, also called even division or consensus division, is a division of a heterogeneous resource ("cake") to several subsets such that each of n people with different tastes agree about the valuations of the pieces.

Fair cake-cutting 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 subjectively fair, in that each person should receive a piece that he or she believes 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 Robertson–Webb protocol is a protocol for envy-free cake-cutting which is also near-exact. It has the following properties:

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

An equitable division (EQ) is a division of a heterogeneous object, 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:

Fair item allocation is a kind of a fair division problem in which the items to divide are discrete rather than continuous. The items have to be divided among several partners who value them differently, and each item has to be given as a whole to a single person. This situation arises in various real-life scenarios:

Envy-freeness (EF) is a criterion of fair division. In an envy-free division, every agent feels that their share is at least as good as the share of any other agent, and thus no agent feels envy.

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 inspired by the utilitarian philosophy. Utilitarian cake-cutting is often not "fair"; hence, utilitarianism is in conflict with fair cake-cutting.

Rental harmony is a kind of a fair division problem in which indivisible items and a fixed monetary cost have to be divided simultaneously. The housemates problem and room-assignment-rent-division are alternative names to the same problem.

Envy-free item allocation is a fair item allocation problem, in which the fairness criterion is envy-freeness - each agent should receive a bundle that he believes to be at least as good as the bundle of any other agent.

The lone divider procedure is a procedure for proportional cake-cutting. It involves a 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 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.

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.

Maximin share (MMS) is a criterion of fair item allocation. Given a set of items with different values, the 1-out-of-n maximin-share is the maximum value that can be gained by partitioning the items into n parts and taking the part with the minimum value.

References

  1. Aumann, Robert J.; Maschler, Michael (1985). "Game Theoretic Analysis of a bankruptcy Problem from the Talmud" (PDF). Journal of Economic Theory. 36: 195–213. doi:10.1016/0022-0531(85)90102-4. Archived from the original (PDF) on 2006-02-20.
  2. Yaari, M. E.; Bar-Hillel, M. (1984). "On dividing justly". Social Choice and Welfare. 1: 1. doi:10.1007/BF00297056.
  3. Manurangsi, Pasin; Suksompong, Warut (2017). "Asymptotic Existence of Fair Divisions for Groups". Mathematical Social Sciences. 89: 100–108. arXiv: 1706.03184 . doi:10.1016/j.mathsocsci.2017.05.006.
  4. Suksompong, Warut (2018). "Approximate Maximin Shares for Groups of Agents". Mathematical Social Sciences. 92: 40–47. arXiv: 1706.09869 . doi:10.1016/j.mathsocsci.2017.09.004.
  5. Sol Garfunkel. More Equal than Others: Weighted Voting. For All Practical Purposes. COMAP. 1988
  6. Mathematical Snapshots. H.Steinhaus. 1950, 1969 ISBN   0-19-503267-5
  7. aha! Insight. Martin. Gardner, 1978. ISBN   978-0-7167-1017-2
  8. How to cut a cake and other mathematical conundrums. Ian Stewart. 2006. ISBN   978-0-19-920590-5
  9. http://www.qwantz.com/index.php?comic=1345