4,215 research outputs found
A constraint programming approach to the hospitals/residents problem
An instance I of the Hospitals/Residents problem (HR) involves a set of residents (graduating medical students) and a set of hospitals, where each hospital has a given capacity. The residents have preferences for the hospitals, as do hospitals for residents. A solution of I is a <i>stable matching</i>, which is an assignment of residents to hospitals that respects the capacity conditions and preference lists in a precise way. In this paper we present constraint encodings for HR that give rise to important structural properties. We also present a computational study using both randomly-generated and real-world instances. We provide additional motivation for our models by indicating how side constraints can be added easily in order to solve hard variants of HR
A Constraint Programming Approach to the Hospitals / Residents Problem
An instance I of the Hospitals / Residents problem (HR) involves a set of residents
(graduating medical students) and a set of hospitals, where each hospital has a given
capacity. The residents have preferences for the hospitals, as do hospitals for residents.
A solution of I is a stable matching, which is an assignment of residents to hospitals
that respects the capacity conditions and preference lists in a precise way. In this
paper we present constraint encodings for HR that give rise to important structural
properties. We also present a computational study using both randomly-generated
and real-world instances. Our study suggests that Constraint Programming is indeed
an applicable technology for solving this problem, in terms of both theory and practice
New and simple algorithms for stable flow problems
Stable flows generalize the well-known concept of stable matchings to markets
in which transactions may involve several agents, forwarding flow from one to
another. An instance of the problem consists of a capacitated directed network,
in which vertices express their preferences over their incident edges. A
network flow is stable if there is no group of vertices that all could benefit
from rerouting the flow along a walk.
Fleiner established that a stable flow always exists by reducing it to the
stable allocation problem. We present an augmenting-path algorithm for
computing a stable flow, the first algorithm that achieves polynomial running
time for this problem without using stable allocation as a black-box
subroutine. We further consider the problem of finding a stable flow such that
the flow value on every edge is within a given interval. For this problem, we
present an elegant graph transformation and based on this, we devise a simple
and fast algorithm, which also can be used to find a solution to the stable
marriage problem with forced and forbidden edges.
Finally, we study the stable multicommodity flow model introduced by
Kir\'{a}ly and Pap. The original model is highly involved and allows for
commodity-dependent preference lists at the vertices and commodity-specific
edge capacities. We present several graph-based reductions that show
equivalence to a significantly simpler model. We further show that it is
NP-complete to decide whether an integral solution exists
Mean-Field Games for Marriage
This article examines mean-field games for marriage. The results support the
argument that optimizing the long-term well-being through effort and social
feeling state distribution (mean-field) will help to stabilize marriage.
However, if the cost of effort is very high, the couple fluctuates in a bad
feeling state or the marriage breaks down. We then examine the influence of
society on a couple using mean field sentimental games. We show that, in
mean-field equilibrium, the optimal effort is always higher than the one-shot
optimal effort. We illustrate numerically the influence of the couple's network
on their feeling states and their well-being.Comment: 22 figures. Accepted and to appear in PLoS On
A Generalization of the AL method for Fair Allocation of Indivisible Objects
We consider the assignment problem in which agents express ordinal
preferences over objects and the objects are allocated to the agents based
on the preferences. In a recent paper, Brams, Kilgour, and Klamler (2014)
presented the AL method to compute an envy-free assignment for two agents. The
AL method crucially depends on the assumption that agents have strict
preferences over objects. We generalize the AL method to the case where agents
may express indifferences and prove the axiomatic properties satisfied by the
algorithm. As a result of the generalization, we also get a speedup on
previous algorithms to check whether a complete envy-free assignment exists or
not. Finally, we show that unless P=NP, there can be no polynomial-time
extension of GAL to the case of arbitrary number of agents
Lazy Model Expansion: Interleaving Grounding with Search
Finding satisfying assignments for the variables involved in a set of
constraints can be cast as a (bounded) model generation problem: search for
(bounded) models of a theory in some logic. The state-of-the-art approach for
bounded model generation for rich knowledge representation languages, like ASP,
FO(.) and Zinc, is ground-and-solve: reduce the theory to a ground or
propositional one and apply a search algorithm to the resulting theory.
An important bottleneck is the blowup of the size of the theory caused by the
reduction phase. Lazily grounding the theory during search is a way to overcome
this bottleneck. We present a theoretical framework and an implementation in
the context of the FO(.) knowledge representation language. Instead of
grounding all parts of a theory, justifications are derived for some parts of
it. Given a partial assignment for the grounded part of the theory and valid
justifications for the formulas of the non-grounded part, the justifications
provide a recipe to construct a complete assignment that satisfies the
non-grounded part. When a justification for a particular formula becomes
invalid during search, a new one is derived; if that fails, the formula is
split in a part to be grounded and a part that can be justified.
The theoretical framework captures existing approaches for tackling the
grounding bottleneck such as lazy clause generation and grounding-on-the-fly,
and presents a generalization of the 2-watched literal scheme. We present an
algorithm for lazy model expansion and integrate it in a model generator for
FO(ID), a language extending first-order logic with inductive definitions. The
algorithm is implemented as part of the state-of-the-art FO(ID) Knowledge-Base
System IDP. Experimental results illustrate the power and generality of the
approach
Core many-to-one matchings by fixed-point methods
We characterize the core many-to-one matchings as fixed points of a map. Our characterization gives an algorithm for finding core allocations; the algorithm is efficient and simple to implement. Our characterization does not require substitutable preferences, so it is separate from the structure needed for the non-emptiness of the core. When preferences are substitutable, our characterization gives a simple proof of the lattice structure of core matchings, and it gives a method for computing the join and meet of two core matchings
- …