Price of fairness

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In the theory of fair division, the price of fairness (POF) is the ratio of the largest economic welfare attainable by a division to the economic welfare attained by a fair division. The POF is a quantitative measure of the loss of welfare that society has to take in order to guarantee fairness.

Contents

In general, the POF is defined by the following formula:

The exact price varies greatly based on the kind of division, the kind of fairness and the kind of social welfare we are interested in.

The most well-studied type of social welfare is utilitarian social welfare , defined as the sum of the (normalized) utilities of all agents. Another type is egalitarian social welfare , defined as the minimum (normalized) utility per agent.

Numeric example

In this example we focus on the utilitarian price of proportionality , or UPOP.

Consider a heterogeneous land-estate that has to be divided among 100 partners, all of whom value it as 100 (or the value is normalized to 100). First, let's look at some extreme cases.

Upper bound

The extreme cases described above already give us a trivial upper bound: UPOP ≤ 10000/100 = 100. But we can get a tighter upper bound.

Assume that we have an efficient division of a land-estate to 100 partners, with a utilitarian welfare U. We want to convert it to a proportional division. To do this, we group the partners according to their current value:

There are two cases:

To summarize: the UPOP is always less than 20, regardless of the value measures of the partners.

Lower bound

The UPOP can be as low as 1. For example, if all partners have the same value measure, then in any division, regardless of fairness, the utilitarian welfare is 100. Hence, UPOP=100/100=1.

However, we are interested on a worst-case UPOP, i.e., a combination of value measures in which the UPOP is large. Here is such an example.

Assume there are two types of partners:

Consider the two following partitions:

In this example, the UPOP is 1000/190=5.26. Thus 5.26 is a lower bound on the worst-case UPOP (where the "worst-case" is taken over all possible combinations of value measures).

Combined

Combining all the results, we get that the worst-case UPOP is bounded between 5 and 20.

This example is typical of the arguments used to bound the POF. To prove a lower bound, it is sufficient to describe a single example; to prove an upper bound, an algorithm or another sophisticated argument should be presented.

Cake-cutting with general pieces

Utilitarian price of proportionality

The numeric example described above can be generalized from 100 to n partners, giving the following bounds for the worst-case UPOP:

n/2 ≤ UPOP ≤ 2√n-1
UPOP = Θ(√n)

For two partners, a more detailed calculation gives a bound of: 8-4*√3 ≅ 1.07. [1]

Utilitarian price of envy

When the entire cake is divided, an envy-free division is always proportional. Hence the lower bound on the worst-case UPOP (√n/2) applies here too. On the other hand, as an upper bound we only have a weak bound of n-1/2. [1] Hence:

n/2 ≤ UPOV ≤ n-1/2
Ω(√n) ≤ UPOV ≤ O(n)

For two partners, a more detailed calculation gives a bound of: 8-4*√3 ≅ 1.07. [1]

Utilitarian price of equitability

For two partners, a more detailed calculation gives a bound of: 9/8=1.125. [1]

Indivisible goods allocation

For indivisible items, an assignment satisfying proportionality, envy-freeness, or equitability does not always exist (for a simple example, imagine two partners trying to divide a single valuable item). See also fair item allocation. Consequently, in the price of fairness calculations, the instances in which no assignment satisfies the relevant fairness notion are not considered. A brief summary of the results: [1]

UPOP = n - 1 + 1/n; for two people: 3/2.
(3n+7)/9-O(1/n) ≤ UPOV ≤ n-1/2; for two people: 3/2
UPOQ=Infinity; for two people: 2

Chore-cutting with general pieces

For the problem of cake-cutting when the "cake" is undesirable (e.g. lawn-mowing), we have the following results: [1]

(n+1)^2/4n ≤ UPOP ≤ n; for two people: 9/8
(n+1)^2/4n ≤ UPOV ≤ infinity; for two people: 9/8
UPOQ=n

Indivisible bads allocation

UPOP = n
UPOV = infinity
UPOQ = infinity

Cake-cutting with connected pieces

The problem of fair cake-cutting has a variation in which the pieces must be connected. In this variation, both the nominator and the denominator in the POF formula are smaller (since the maximum is taken over a smaller set), so a priori it is not clear whether the POF should be smaller or larger than in the disconnected case.

Utilitarian price of fairness

We have the following results for utilitarian welfare: [2]

UPOP = Θ(√n)
UPOV = Θ(√n)
n-1+1/n ≤ EPOQ ≤ n
EPOQ = Θ(n)

Egalitarian price of fairness

In a proportional division, the value of each partner is at least 1/n of the total. In particular, the value of the least fortunate agent (which is called the egalitarian welfare of the division) is at least 1/n. This means that in an egalitarian-optimal division, the egalitarian welfare is at least 1/n, and so an egalitarian-optimal division is always proportional. Hence, the egalitarian price of proportionality (EPOP) is 1:

EPOP = 1

Similar considerations apply to the egalitarian price of equitability (EPOQ):

EPOQ = 1

The egalitarian price of envy-freeness is much larger: [2]

EPOV = n/2

This is an interesting result, as it implies that insistence on the criterion of envy-freeness increases the social gaps and harms the most unfortunate citizens. The criterion of proportionality is much less harmful.

Price of welfare-maximization

Instead of calculating the loss of welfare due to fairness, we can calculate the loss of fairness due to welfare optimization. We get the following results: [2]

proportional-price-of-egalitarianism = 1
envy-price-of-egalitarianism = n-1
proportional-price-of-utilitarianism = infinity
envy-price-of-egalitarianism = infinity

Indivisible goods allocation with connected blocks

As in cake-cutting, for indivisible item assignment there is a variation where the items lie on a line and each assigned piece must form a block on the line. A brief summary of the results: [3]

UPOP = n - 1 + 1/n
UPOV = Θ(√n)
UPOQ = infinity; for two people: 3/2
EPOP = 1
EPOV = n/2
EPOQ = infinity; for two people: 1

Chore-cutting with connected pieces

A brief summary of the results: [4]

n/2 ≤ UPOP ≤ n
UPOV = infinity
UPOQ = n
EPOP = 1
EPOV = infinity
EPOQ = 1

Homogeneous resource allocation

The price of fairness has also been studied in the contest of the allocation of homogeneous divisible resources, such as oil or woods. Known results are: [5] [6]

UPOV = UPOP = Θ(√n)

This is because the rule of competitive equilibrium from equal incomes yields an envy-free allocation, and its utilitarian price is O(√n).

Other contexts

The price-of-fairness has been studied in the context of the fair subset sum problem.

The price of justified representation is the loss in the average satisfaction due to the requirement to have a justified representation in an approval voting setting. [7]

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.

<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:

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:

Fair item allocation is a kind of the fair division problem in which the items to divide are discrete rather than continuous. The items have to be divided among several partners who potentially 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:

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.

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.

Resource monotonicity is a principle of fair division. It says that, if there are more resources to share, then all agents should be weakly better off; no agent should lose from the increase in resources. The RM principle has been studied in various division problems.

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.

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.

When allocating objects among people with different preferences, two major goals are Pareto efficiency and fairness. Since the objects are indivisible, there may not exist any fair allocation. For example, when there is a single house and two people, every allocation of the house will be unfair to one person. Therefore, several common approximations have been studied, such as maximin-share fairness (MMS), envy-freeness up to one item (EF1), proportionality up to one item (PROP1), and equitability up to one item (EQ1). The problem of efficient approximately fair item allocation is to find an allocation that is both Pareto-efficient (PE) and satisfies one of these fairness notions. The problem was first presented at 2016 and has attracted considerable attention since then.

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:

The multiple subset sum problem is an optimization problem in computer science and operations research. It is a generalization of the subset sum problem. The input to the problem is a multiset of n integers and a positive integer m representing the number of subsets. The goal is to construct, from the input integers, some m subsets. The problem has several variants:

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:

Fair allocation of items and money is a class of fair item allocation problems in which, during the allocation process, it is possible to give or take money from some of the participants. Without money, it may be impossible to allocate indivisible items fairly. For example, if there is one item and two people, and the item must be given entirely to one of them, the allocation will be unfair towards the other one. Monetary payments make it possible to attain fairness, as explained below.

References

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  2. 1 2 3 Aumann, Y.; Dombb, Y. (2010). "The Efficiency of Fair Division with Connected Pieces" . Internet and Network Economics. Lecture Notes in Computer Science. Vol. 6484. pp.  26. CiteSeerX   10.1.1.391.9546 . doi:10.1007/978-3-642-17572-5_3. ISBN   978-3-642-17571-8.
  3. Suksompong, W. (2019). "Fairly Allocating Contiguous Blocks of Indivisible Items". Discrete Applied Mathematics. 260: 227–236. arXiv: 1707.00345 . doi:10.1016/j.dam.2019.01.036. S2CID   126658778.
  4. Heydrich, S.; van Stee, R. (2015). "Dividing Connected Chores Fairly". Theoretical Computer Science. 593: 51–61. doi: 10.1016/j.tcs.2015.05.041 . hdl: 2381/37387 .
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  7. Elkind, Edith; Faliszewski, Piotr; Igarashi, Ayumi; Manurangsi, Pasin; Schmidt-Kraepelin, Ulrike; Suksompong, Warut (2021-12-13). "The Price of Justified Representation". arXiv: 2112.05994 [cs.GT].