Fair Division Research Articles

In the envy-free cake-cutting problem, we are given a resource, usually called a cake and represented as the [0,1] interval, and a set of n agents with heterogeneous preferences over pieces of the cake. The goal is to divide the cake among the n agents such that no agent is envious of any other agent. Even under a very general preferences model, this fundamental fair division problem is known to always admit an exact solution where each agent obtains a connected piece of the cake; we study the complexity of finding an approximate solution, i.e., a connected ɛ-envy-free allocation. For monotone valuations of cake pieces, Deng, Qi, and Saberi (2012) gave an efficient (poly(log (1/ɛ)) queries) algorithm for three agents and posed the open problem of four (or more) monotone agents. Even for the special case of additive valuations, Brânzei and Nisan (2022) conjectured an Ω (1/ɛ) lower bound on the number of queries for four agents. We provide the first efficient algorithm for finding a connected ɛ-envy-free allocation with four monotone agents. We also prove that as soon as valuations are allowed to be non-monotone , the problem becomes hard: it becomes PPAD -hard, requires poly(1/ɛ) queries in the black-box model, and even poly(1/ɛ) communication complexity . This constitutes, to the best of our knowledge, the first intractability result for any version of the cake-cutting problem in the communication complexity model.

Differentially private fair division

Abstract We divide efficiently a pile of indivisible goods in common property, using cash transfers to ensure fairness among agents with utility linear in money. We compare three cognitively feasible and privacy preserving division rules in terms of the guarantees (worst case utility) they offer to the participants. In the first version of Divide & Choose to n agents, they bid for the role of Divider then everyone bids on the shares of the Divider’s partition. In the second version each agent announces a partition and they all bid to select the most efficient one. In the Bid & Sell rule the agents bid for the role of Seller: with two agents the smallest bid defines the Seller who then charges any price constrained only by her winning bid. Both rules reward subadditive utilities and penalise superadditive ones, and B&S more so than both D&C-s. B&S is also better placed to collect a larger share of the surplus when agents play safe.

Communication in the family plays a very important role in maintaining harmonious relationships between family members. In this case, the dynamics of communication between husband and wife often reflect social changes that occur in society. One interesting phenomenon to study is the dominance of communication by the wife in the family, which is influenced by social, cultural, educational, and economic factors. This study focuses on the community of Ranah Batahan District, West Sumatra, using a qualitative approach and case study design. Data collection was carried out through interviews, observations, and documentation, which were then analyzed using an interactive model and a phenomenological approach. The conclusions of the study were drawn inductively. The results of the study showed that the dominance of wife communication was influenced by economic factors (the wife as the main breadwinner), education, and the husband's passive or less assertive character. From an Islamic perspective, the wife's dominance in family communication does not conflict with the sharia, as long as it maintains the principles of deliberation, mutual respect, and fair division of roles according to the couple's abilities. Islam emphasizes justice, not domination, in household relationships. This finding confirms that the wife's dominance in communication is acceptable in Islam, as long as it does not cause an imbalance in responsibility and maintains family harmony in accordance with the guidance of the Qur'an and Sunnah.

The purpose of this study is to find out how the Implementation of Learning Environment Management in SD Alkhairaat 2 Palu Schools. This research uses a descriptive approach or a qualitative approach. The subjects in this study are the principal, teachers and fifth grade students of SD Alkhairaat 2 Palu. The data collection techniques used are observation, documentation, and interviews. The analysis used is data collection, data reduction, data presentation, and verification or drawing conclusions. The results of the study show that the management of the physical environment of the classroom has been well implemented, where the teacher involves students in the arrangement of the classroom to create a comfortable and effective learning atmosphere. The application of discipline in managing learning shows the efforts of teachers and principals as examples, although there are still challenges in student discipline. Good communication between teachers and students is built through an open approach, creating harmonious relationships and a positive learning atmosphere. An effective classroom organization is formed through a fair division of tasks, increasing student responsibility. Overall, the management of the learning environment at SD Alkhairaat 2 Palu has been well implemented, although the challenges in maintaining students' focus on learning still need further attention.

Fair division with subjective divisibility

Ordinal maximin guarantees for group fair division

This research examines the perception of Generation Z and Millennials regarding marital joint property (harta gono-gini), a crucial issue in Indonesian marriage law. Using a combination of qualitative and quantitative methods, this study seeks to uncover how these two generations view the division of joint assets after divorce. The results show that Gen Z and Millennials tend to prioritize fair and equitable distribution based on individual contributions during the marriage. However, differences emerge between the two generations in terms of approaches to conflict resolution, where Millennials are more likely to choose mediation, while Gen Z tends to prefer negotiation as a resolution strategy. Furthermore, the study finds that gender also plays a role in shaping perceptions of joint property, with men generally favoring individual ownership, while women emphasize joint ownership and fair division. This research contributes to a better understanding of generational and gender differences in views on joint property in marriage. It also has practical implications for legal practitioners and policymakers in developing more effective conflict resolution frameworks related to marital joint property.

We study fair mechanisms for the classic job scheduling problem on unrelated machines with the objective of minimizing the makespan. This problem is equivalent to minimizing the egalitarian social cost in the fair division of chores. The two prevalent fairness notions in the fair division literature are envy-freeness and proportionality. Prior work has established that no envy-free mechanism can provide better than an Ω(log m / log log m)-approximation to the optimal makespan, where m is the number of machines, even when payments to the machines are allowed. In strong contrast to this impossibility, our main result demonstrates that there exists a proportional mechanism (with payments) that achieves a 3/2-approximation to the optimal makespan, and this ratio is tight. To prove this result, we provide a full characterization of allocation functions that can be made proportional with payments. Furthermore, we show that for instances with normalized costs, there exists a proportional mechanism that achieves the optimal makespan. We conclude with important directions for future research concerning other fairness notions, including relaxations of envy-freeness. Notably, we show that the technique leading to the impossibility result for envy-freeness does not extend to its relaxations.

We introduce a model of fair division with market values, where indivisible goods must be partitioned among agents with (additive) subjective valuations, and each good additionally has a market value. The market valuation can be viewed as a separate additive valuation that holds identically across all the agents. We seek allocations that are simultaneously fair with respect to the subjective valuations and under the market valuation. We show that an allocation that satisfies stochastically-dominant envy-freeness up to one good (SD-EF1) with respect to both the subjective valuations and the market valuation does not always exist, but the weaker guarantee of EF1 with respect to the subjective valuations along with SD-EF1 with respect to the market valuation can be guaranteed. We also study a number of other guarantees such as Pareto optimality, EFX, and MMS. In addition, we explore non-additive valuations and extend our model to cake-cutting. Along the way, we identify several tantalizing open questions.

We study the fundamental problem of fairly dividing a set of indivisible items among agents with (general) monotone valuations. The notion of envy-freeness up to any item (EFX) is considered to be one of the most fascinating fairness concepts in this line of work. Unfortunately, despite significant efforts, existence of EFX allocations is a major open problem in fair division, thereby making the study of approximations and relaxations of EFX a natural line of research. Recently, Caragiannis et al. [2023] introduced a promising relaxation of EFX, called epistemic EFX (EEFX). An allocation is EEFX, if for every agent, it is possible to shuffle the items in the remaining bundles so that she becomes ``EFX-satisfied''. Caragiannis et al. [2023] prove existence and polynomial-time computability of EEFX allocations for additive valuations. A natural question asks what happens when we consider valuations more general than additive? We address this important open question and answer it affirmatively by establishing the existence of EEFX allocations for an arbitrary number of agents with general monotone valuations. To the best of our knowledge, besides EF1, EEFX is the only known relaxation of EFX to have such strong existential guarantees. Furthermore, we complement our existential result by proving computational and information-theoretic lower bounds. We prove that even for an arbitrary number of (more than one) agents with identical submodular valuations, it is PLS-hard to compute EEFX allocations and it requires exponentially-many value queries to do so.

In this paper, we consider the problem of fair division of indivisible goods, where the allocation of goods impacts society. Specifically, we introduce a second valuation function for each agent, which determines the social impact of allocating a good to the agent. Such impact is considered desirable for the society -- the higher, the better. Our goal is to understand how to allocate goods fairly from the agents' perspective while maintaining society as happy as possible. To this end, we measure the impact on society using the utilitarian social welfare, and provide both possibility and impossibility results. Our findings reveal that achieving good approximations, better than linear in the number of agents, is not possible while ensuring fairness to the agents. These impossibility results can be attributed to the fact that agents are completely unconscious of their social impact. Consequently, we explore scenarios where agents are socially aware, by introducing related fairness notions, and demonstrate that an appropriate definition of fairness is compatible with the social objective.

In this paper, we consider the classic fair division problem of allocating m divisible items to n agents with linear valuations over the items. We define novel notions of fair shares from the perspective of individual agents via the cake-cutting process. These shares generalize the notion of proportionality by taking into account the valuations of other agents via constraints capturing envy. We study what fraction (approximation) of these shares are achievable in the worst case, and present tight and non-trivial approximation bounds as a function of n and m. In particular, we show a tight approximation bound of Θ(√n) for various notions of such shares. We show this bound via a novel application of dual fitting, which may be of independent interest. We also present a bound of O(m^(2/3)) for a strict notion of share, with an almost matching lower bound. We further develop weaker notions of shares whose approximation bounds interpolate smoothly between proportionality and the shares described above. We finally present empirical results showing that our definitions lead to more reasonable shares than the standard fair share notion of proportionality.

In the recently introduced model of fair partitioning of friends, there is a set of agents located on the vertices of an underlying graph that indicates the friendships between the agents. The task is to partition the graph into k balanced-sized groups, keeping in mind that the value of an agent for a group is equal to the number of edges they have in that group. The goal is to construct partitions that are "fair", i.e., no agent would like to replace an agent in a different group. We generalize the standard model by considering utilities for the agents that are beyond binary and additive. Having this as our foundation, our contribution is threefold: (a) we adapt several fairness notions that have been developed in the fair division literature to our setting; (b) we give several existence guarantees supported by polynomial-time algorithms; (c) we initiate the study of the computational (and parameterized) complexity of the model and provide an almost complete landscape of the (in)tractability frontier for our fairness concepts.

We study temporal fair division, whereby a set of agents are allocated a (possibly different) set of goods on each day for a period of days. We study this setting, as well as a number of its special cases formed by the restrictions to two agents, same goods on each day, identical preferences, or combinations thereof, and chart out the landscape of achieving two types of fairness guarantees simultaneously: fairness on each day (per day) and fairness over time (up to each day, or the weaker version, overall). In the most general setting, we prove that there always exists an allocation that is stochastically-dominant envy-free up to one good (SD-EF1) per day and proportional up to one good (PROP1) overall, and when all the agents have identical preferences, we show that SD-EF1 per day and SD-EF1 overall can be guaranteed. For the case of two agents, we prove that SD-EF1 per day and EF1 up to each day can be guaranteed using an envy balancing technique. We provide counterexamples for other combinations that establish our results as among the best guarantees possible, but also leave open some tantalizing questions.

Fairness and efficiency have become the pillars of modern fair division research, but prior work on achieving both simultaneously is largely limited to the unconstrained setting. We study fair and efficient allocations of indivisible goods under additive valuations and various types of allocation feasibility constraints, and demonstrate the unreasonable effectiveness of the maximum Nash welfare (MNW) solution in this previously uncharted territory. Our main result is that MNW allocations are 1/2-envy-free up to one good (EF1) and Pareto optimal under the broad family of (arbitrary) matroid constraints. We extend these guarantees to complete MNW allocations for base-orderable matroid constraints, and to a family of non-matroid constraints (which includes balancedness). We establish tightness of our results by providing counterexamples for the satisfiability of certain stronger desiderata, but show an improved result for the special case of goods with copies (Gafni et al. 2023). Finally, we also establish novel best-of-both-worlds guarantees for goods with copies and balancedness.

We study fair division of indivisible chores among n agents with additive cost functions using the popular fairness notion of maximin share (MMS). Since MMS allocations do not always exist for more than two agents, the goal has been to improve its approximations and identify interesting special cases where MMS allocations exist. We show the existence of · 1-out-of-9n/11 MMS allocations, which improves the state-of-the-art factor of 1-out-of-3n/4. · MMS allocations for factored instances, which resolves an open question posed by Ebadian et al. (2021). · 15/13-MMS allocations for personalized bivalued instances, improving the state-of-the-art factor of 13/11. We achieve these results by leveraging the HFFD algorithm of Huang and Lu (2021). Our approach also provides polynomial-time algorithms for computing an MMS allocation for factored instances and a 15/13-MMS allocation for personalized bivalued instances.

We formulate the problem of fair and efficient completion of indivisible goods, defined as follows: Given a partial allocation of indivisible goods among agents, does there exist an allocation of the remaining goods (i.e., a completion) that satisfies fairness and economic efficiency guarantees of interest? We study the computational complexity of the completion problem for prominent fairness and efficiency notions such as envy-freeness up to one good (EF1), proportionality up to one good (Prop1), maximin share (MMS), and Pareto optimality (PO), and focus on the class of additive valuations as well as its subclasses such as binary additive and lexicographic valuations. We find that while the completion problem is significantly harder than the standard fair division problem (wherein the initial partial allocation is empty), the consideration of restricted preferences facilitates positive algorithmic results for threshold-based fairness notions (Prop1 and MMS). On the other hand, the completion problem remains computationally intractable for envy-based notions such as EF1 and EF1+PO even under restricted preferences.

We study online fair division when there are a finite number of item types and the player values for the items are drawn randomly from distributions with unknown means. In this setting, a sequence of indivisible items arrives according to a random online process, and each item must be allocated to a single player. The goal is to maximize expected social welfare while maintaining that the allocation satisfies proportionality in expectation. When player values are normalized, we show that it is possible to with high probability guarantee proportionality constraint satisfaction and achieve O(√T) regret. To achieve this result, we present an upper confidence bound (UCB) algorithm that uses two rounds of linear optimization. This algorithm highlights fundamental aspects of proportionality constraints that allow for a UCB algorithm despite the presence of many (potentially tight) constraints. This result improves upon the previous best regret rate of O(T^(2/3)).

Currently, a global hunger and malnutrition crisis is spreading throughout various regions worldwide. Overseas farmland investment endeavors to enhance regional food production through international cooperation but faces the challenge of ensuring a fair division. Our study develops a more equitable method: we have modeled overseas farmland investment as a cooperative game, reallocating benefits among host countries and investing countries. The application of our results to real data indicates that there is not only significant scope for improvement for host countries and overseas investors—which gain added benefits—but also a remarkable contribution made to rural development in terms of increased productivity. The cooperation to increase farmland yield through technology and capital transfer can be achieved in practice. In this context, transnational cooperations can provide additional benefits to participants, which can offer an important motivation for collaborators.