Algorithms for Competitive Division of Chores
July 03, 2019 Β· Declared Dead Β· π Mathematics of Operations Research
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Simina BrΓ’nzei, Fedor Sandomirskiy
arXiv ID
1907.01766
Category
cs.GT: Game Theory
Cross-listed
cs.DS,
econ.TH
Citations
41
Venue
Mathematics of Operations Research
Last Checked
6 months ago
Abstract
We study the problem of allocating divisible bads (chores) among multiple agents with additive utilities when monetary transfers are not allowed. The competitive rule is known for its remarkable fairness and efficiency properties in the case of goods. This rule was extended to chores in prior work by Bogomolnaia, Moulin, Sandomirskiy, and Yanovskaya (2017). The rule produces Pareto optimal and envy-free allocations for both goods and chores. In the case of goods, the outcome of the competitive rule can be easily computed. Competitive allocations solve the Eisenberg-Gale convex program; hence the outcome is unique and can be approximately found by standard gradient methods. An exact algorithm that runs in polynomial time in the number of agents and goods was given by Orlin (2010). In the case of chores, the competitive rule does not solve any convex optimization problem; instead, competitive allocations correspond to local minima, local maxima, and saddle points of the Nash social welfare on the Pareto frontier of the set of feasible utilities. The Pareto frontier may contain many such points; consequently, the competitive rule's outcome is no longer unique. In this paper, we show that all the outcomes of the competitive rule for chores can be computed in strongly polynomial time if either the number of agents or the number of chores is fixed. The approach is based on a combination of three ideas: all consumption graphs of Pareto optimal allocations can be listed in polynomial time; for a given consumption graph, a candidate for a competitive utility profile can be constructed via an explicit formula; each candidate can be checked for competitiveness, and the allocation can be reconstructed using a maximum flow computation. Our algorithm gives an approximately-fair allocation of indivisible chores by the rounding technique of Barman and Krishnamurthy (2018).
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Game Theory
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
A Motivational Game-Theoretic Approach for Peer-to-Peer Energy Trading in the Smart Grid
R.I.P.
π»
Ghosted
Computing Resource Allocation in Three-Tier IoT Fog Networks: a Joint Optimization Approach Combining Stackelberg Game and Matching
R.I.P.
π»
Ghosted
Fast Convergence of Regularized Learning in Games
R.I.P.
π»
Ghosted
Computation Peer Offloading for Energy-Constrained Mobile Edge Computing in Small-Cell Networks
R.I.P.
π»
Ghosted
Blockchain Mining Games
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted