244 research outputs found
Chore division on a graph
The paper considers fair allocation of indivisible nondisposable items that
generate disutility (chores). We assume that these items are placed in the
vertices of a graph and each agent's share has to form a connected subgraph of
this graph. Although a similar model has been investigated before for goods, we
show that the goods and chores settings are inherently different. In
particular, it is impossible to derive the solution of the chores instance from
the solution of its naturally associated fair division instance. We consider
three common fair division solution concepts, namely proportionality,
envy-freeness and equitability, and two individual disutility aggregation
functions: additive and maximum based. We show that deciding the existence of a
fair allocation is hard even if the underlying graph is a path or a star. We
also present some efficiently solvable special cases for these graph
topologies
Fairly Allocating Contiguous Blocks of Indivisible Items
In this paper, we study the classic problem of fairly allocating indivisible
items with the extra feature that the items lie on a line. Our goal is to find
a fair allocation that is contiguous, meaning that the bundle of each agent
forms a contiguous block on the line. While allocations satisfying the
classical fairness notions of proportionality, envy-freeness, and equitability
are not guaranteed to exist even without the contiguity requirement, we show
the existence of contiguous allocations satisfying approximate versions of
these notions that do not degrade as the number of agents or items increases.
We also study the efficiency loss of contiguous allocations due to fairness
constraints.Comment: Appears in the 10th International Symposium on Algorithmic Game
Theory (SAGT), 201
Nearly Equitable Allocations Beyond Additivity and Monotonicity
Equitability (EQ) in fair division requires that items be allocated such that
all agents value the bundle they receive equally. With indivisible items, an
equitable allocation may not exist, and hence we instead consider a meaningful
analog, EQx, that requires equitability up to any item. EQx allocations exist
for monotone, additive valuations. However, if (1) the agents' valuations are
not additive or (2) the set of indivisible items includes both goods and chores
(positively and negatively valued items), then prior to the current work it was
not known whether EQx allocations exist or not.
We study both the existence and efficient computation of EQx allocations. (1)
For monotone valuations (not necessarily additive), we show that EQx
allocations always exist. Also, for the large class of weakly well-layered
valuations, EQx allocations can be found in polynomial time. Further, we prove
that approximately EQx allocations can be computed efficiently under general
monotone valuations. (2) For non-monotone valuations, we show that an EQx
allocation may not exist, even for two agents with additive valuations. Under
some special cases, however, we establish existence and efficient computability
of EQx allocations. This includes the case of two agents with additive
valuations where each item is either a good or a chore, and there are no mixed
items. In addition, we show that, under nonmonotone valuations, determining the
existence of EQx allocations is weakly NP-hard for two agents and strongly
NP-hard for more agents.Comment: 28 page
Chore division on a graph
Le PDF est une version non publiée datant de 2018.International audienceThe paper considers fair allocation of indivisible nondisposable items that generate disutility (chores). We assume that these items are placed in the vertices of a graph and each agent’s share has to form a connected subgraph of this graph. Although a similar model has been investigated before for goods, we show that the goods and chores settings are inherently different. In particular, it is impossible to derive the solution of the chores instance from the solution of its naturally associated fair division instance. We consider three common fair division solution concepts, namely proportionality, envy-freeness and equitability, and two individual disutility aggregation functions: additive and maximum based. We show that deciding the existence of a fair allocation is hard even if the underlying graph is a path or a star. We also present some efficiently solvable special cases for these graph topologies
Envy-free Relaxations for Goods, Chores, and Mixed Items
In fair division problems, we are given a set of items and a set
of agents with individual preferences, and the goal is to find an
allocation of items among agents so that each agent finds the allocation fair.
There are several established fairness concepts and envy-freeness is one of the
most extensively studied ones. However envy-free allocations do not always
exist when items are indivisible and this has motivated relaxations of
envy-freeness: envy-freeness up to one item (EF1) and envy-freeness up to any
item (EFX) are two well-studied relaxations. We consider the problem of finding
EF1 and EFX allocations for utility functions that are not necessarily
monotone, and propose four possible extensions of different strength to this
setting.
In particular, we present a polynomial-time algorithm for finding an EF1
allocation for two agents with arbitrary utility functions. An example is given
showing that EFX allocations need not exist for two agents with non-monotone,
non-additive, identical utility functions. However, when all agents have
monotone (not necessarily additive) identical utility functions, we prove that
an EFX allocation of chores always exists. As a step toward understanding the
general case, we discuss two subclasses of utility functions: Boolean utilities
that are -valued functions, and negative Boolean utilities that are
-valued functions. For the latter, we give a polynomial time
algorithm that finds an EFX allocation when the utility functions are
identical.Comment: 21 pages, 1 figur
Fair Allocation based on Diminishing Differences
Ranking alternatives is a natural way for humans to explain their
preferences. It is being used in many settings, such as school choice, course
allocations and residency matches. In some cases, several `items' are given to
each participant. Without having any information on the underlying cardinal
utilities, arguing about fairness of allocation requires extending the ordinal
item ranking to ordinal bundle ranking. The most commonly used such extension
is stochastic dominance (SD), where a bundle X is preferred over a bundle Y if
its score is better according to all additive score functions. SD is a very
conservative extension, by which few allocations are necessarily fair while
many allocations are possibly fair. We propose to make a natural assumption on
the underlying cardinal utilities of the players, namely that the difference
between two items at the top is larger than the difference between two items at
the bottom. This assumption implies a preference extension which we call
diminishing differences (DD), where X is preferred over Y if its score is
better according to all additive score functions satisfying the DD assumption.
We give a full characterization of allocations that are
necessarily-proportional or possibly-proportional according to this assumption.
Based on this characterization, we present a polynomial-time algorithm for
finding a necessarily-DD-proportional allocation if it exists. Using
simulations, we show that with high probability, a necessarily-proportional
allocation does not exist but a necessarily-DD-proportional allocation exists,
and moreover, that allocation is proportional according to the underlying
cardinal utilities. We also consider chore allocation under the analogous
condition --- increasing-differences.Comment: Revised version, based on very helpful suggestions of JAIR referees.
Gaps in some proofs were filled, more experiments were done, and mor
Fair Division of a Graph
We consider fair allocation of indivisible items under an additional
constraint: there is an undirected graph describing the relationship between
the items, and each agent's share must form a connected subgraph of this graph.
This framework captures, e.g., fair allocation of land plots, where the graph
describes the accessibility relation among the plots. We focus on agents that
have additive utilities for the items, and consider several common fair
division solution concepts, such as proportionality, envy-freeness and maximin
share guarantee. While finding good allocations according to these solution
concepts is computationally hard in general, we design efficient algorithms for
special cases where the underlying graph has simple structure, and/or the
number of agents -or, less restrictively, the number of agent types- is small.
In particular, despite non-existence results in the general case, we prove that
for acyclic graphs a maximin share allocation always exists and can be found
efficiently.Comment: 9 pages, long version of accepted IJCAI-17 pape
Fair Allocation of goods and chores -- Tutorial and Survey of Recent Results
Fair resource allocation is an important problem in many real-world
scenarios, where resources such as goods and chores must be allocated among
agents. In this survey, we delve into the intricacies of fair allocation,
focusing specifically on the challenges associated with indivisible resources.
We define fairness and efficiency within this context and thoroughly survey
existential results, algorithms, and approximations that satisfy various
fairness criteria, including envyfreeness, proportionality, MMS, and their
relaxations. Additionally, we discuss algorithms that achieve fairness and
efficiency, such as Pareto Optimality and Utilitarian Welfare. We also study
the computational complexity of these algorithms, the likelihood of finding
fair allocations, and the price of fairness for each fairness notion. We also
cover mixed instances of indivisible and divisible items and investigate
different valuation and allocation settings. By summarizing the
state-of-the-art research, this survey provides valuable insights into fair
resource allocation of indivisible goods and chores, highlighting computational
complexities, fairness guarantees, and trade-offs between fairness and
efficiency. It serves as a foundation for future advancements in this vital
field
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