scholarly journals Weighted Matching Markets with Budget Constraints

2019 ◽  
Vol 65 ◽  
pp. 393-421 ◽  
Author(s):  
Anisse Ismaili ◽  
Naoto Hamada ◽  
Yuzhe Zhang ◽  
Takamasa Suzuki ◽  
Makoto Yokoo
Keyword(s):  
Polynomial Time ◽  
Real World ◽  
Stable Matching ◽  
The Other ◽  
Matching Markets ◽  
Pairwise Stability ◽  
Negative Results ◽  
Strategy Proof ◽  
Pareto Efficient ◽  
Coalitional Stability

We investigate markets with a set of students on one side and a set of colleges on the other. A student and college can be linked by a weighted contract that defines the student's wage, while a college's budget for hiring students is limited. Stability is a crucial requirement for matching mechanisms to be applied in the real world. A standard stability requirement is coalitional stability, i.e., no pair of a college and group of students has any incentive to deviate. We find that a coalitionally stable matching is not guaranteed to exist, verifying the coalitional stability for a given matching is coNP-complete, and the problem of finding whether a coalitionally stable matching exists in a given market, is SigmaP2-complete: NPNP-complete. Other negative results also hold when blocking coalitions contain at most two students and one college. Given these computational hardness results, we pursue a weaker stability requirement called pairwise stability, where no pair of a college and single student has an incentive to deviate. Unfortunately, a pairwise stable matching is not guaranteed to exist either. Thus, we consider a restricted market called a typed weighted market, in which students are partitioned into types that induce their possible wages. We then design a strategy-proof and Pareto efficient mechanism that works in polynomial-time for computing a pairwise stable matching in typed weighted markets.

scholarly journals Matching with floor constraints

2021 ◽  
Vol 16 (3) ◽  
pp. 911-942
Author(s):  
Sumeyra Akin
Keyword(s):  
Additional Condition ◽  
Stable Matching ◽  
Medical Residency ◽  
Matching Markets ◽  
Prominent Feature ◽  
Stable Matchings ◽  
Teacher Assignment ◽  
Is Strategy ◽  
Strategy Proof ◽  
Hard Floor

Floor constraints are a prominent feature of many matching markets, such as medical residency, teacher assignment, and military cadet matching. We develop a theory of matching markets under floor constraints. We introduce a stability notion, which we call floor respecting stability, for markets in which (hard) floor constraints must be respected. A matching is floor respecting stable if there is no coalition of doctors and hospitals that can propose an alternative matching that is feasible and an improvement for its members. Our stability notion imposes the additional condition that a coalition cannot reassign a doctor outside the coalition to another hospital (although she can be fired). This condition is necessary to guarantee the existence of stable matchings. We provide a mechanism that is strategy‐proof for doctors and implements a floor respecting stable matching.

On the Complexity of Deadlock Recovery

1986 ◽  
Vol 9 (3) ◽  
pp. 323-342
Author(s):  
Joseph Y.-T. Leung ◽  
Burkhard Monien
Keyword(s):  
Computational Complexity ◽  
Polynomial Time ◽  
Arbitrary Number ◽  
The Other ◽  
Np Hard ◽  
Total Cost ◽  
Other Hand ◽  
Input Parameters ◽  
Resource Type

We consider the computational complexity of finding an optimal deadlock recovery. It is known that for an arbitrary number of resource types the problem is NP-hard even when the total cost of deadlocked jobs and the total number of resource units are “small” relative to the number of deadlocked jobs. It is also known that for one resource type the problem is NP-hard when the total cost of deadlocked jobs and the total number of resource units are “large” relative to the number of deadlocked jobs. In this paper we show that for one resource type the problem is solvable in polynomial time when the total cost of deadlocked jobs or the total number of resource units is “small” relative to the number of deadlocked jobs. For fixed m ⩾ 2 resource types, we show that the problem is solvable in polynomial time when the total number of resource units is “small” relative to the number of deadlocked jobs. On the other hand, when the total number of resource units is “large”, the problem becomes NP-hard even when the total cost of deadlocked jobs is “small” relative to the number of deadlocked jobs. The results in the paper, together with previous known ones, give a complete delineation of the complexity of this problem under various assumptions of the input parameters.

Improving the External Validity of Conjoint Analysis: The Essential Role of Profile Distribution

2021 ◽  
pp. 1-27 ◽  
Author(s):  
Brandon de la Cuesta ◽  
Naoki Egami ◽  
Kosuke Imai
Keyword(s):  
Conjoint Analysis ◽  
Real World ◽  
External Validity ◽  
Causal Effect ◽  
The Other ◽  
Estimation Methods ◽  
Social Scientists ◽  
Actual Distribution ◽  
Open Source Software Package ◽  
Profile Distribution

Abstract Conjoint analysis has become popular among social scientists for measuring multidimensional preferences. When analyzing such experiments, researchers often focus on the average marginal component effect (AMCE), which represents the causal effect of a single profile attribute while averaging over the remaining attributes. What has been overlooked, however, is the fact that the AMCE critically relies upon the distribution of the other attributes used for the averaging. Although most experiments employ the uniform distribution, which equally weights each profile, both the actual distribution of profiles in the real world and the distribution of theoretical interest are often far from uniform. This mismatch can severely compromise the external validity of conjoint analysis. We empirically demonstrate that estimates of the AMCE can be substantially different when averaging over the target profile distribution instead of uniform. We propose new experimental designs and estimation methods that incorporate substantive knowledge about the profile distribution. We illustrate our methodology through two empirical applications, one using a real-world distribution and the other based on a counterfactual distribution motivated by a theoretical consideration. The proposed methodology is implemented through an open-source software package.

scholarly journals Combining Outcome-Based and Preference-Based Matching: A Constrained Priority Mechanism

2021 ◽  
pp. 1-24
Author(s):  
Avidit Acharya ◽  
Kirk Bansak ◽  
Jens Hainmueller
Keyword(s):  
Machine Learning ◽  
Host Country ◽  
Real World ◽  
Test Scores ◽  
Standardized Test ◽  
Market Design ◽  
Standardized Test Scores ◽  
Real World Data ◽  
Refugee Families ◽  
Strategy Proof

Abstract We introduce a constrained priority mechanism that combines outcome-based matching from machine learning with preference-based allocation schemes common in market design. Using real-world data, we illustrate how our mechanism could be applied to the assignment of refugee families to host country locations, and kindergarteners to schools. Our mechanism allows a planner to first specify a threshold $\bar g$ for the minimum acceptable average outcome score that should be achieved by the assignment. In the refugee matching context, this score corresponds to the probability of employment, whereas in the student assignment context, it corresponds to standardized test scores. The mechanism is a priority mechanism that considers both outcomes and preferences by assigning agents (refugee families and students) based on their preferences, but subject to meeting the planner’s specified threshold. The mechanism is both strategy-proof and constrained efficient in that it always generates a matching that is not Pareto dominated by any other matching that respects the planner’s threshold.

scholarly journals GazeEMD: Detecting Visual Intention in Gaze-Based Human-Robot Interaction

Robotics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 68
Author(s):  
Lei Shi ◽  
Cosmin Copot ◽  
Steve Vanlanduit
Keyword(s):  
Cognitive Load ◽  
Real World ◽  
Robotic Manipulator ◽  
Similarity Score ◽  
Human Robot Interaction ◽  
Experimental Results ◽  
The Other ◽  
Robot Interaction ◽  
Run Length ◽  
The Real

In gaze-based Human-Robot Interaction (HRI), it is important to determine human visual intention for interacting with robots. One typical HRI interaction scenario is that a human selects an object by gaze and a robotic manipulator will pick up the object. In this work, we propose an approach, GazeEMD, that can be used to detect whether a human is looking at an object for HRI application. We use Earth Mover’s Distance (EMD) to measure the similarity between the hypothetical gazes at objects and the actual gazes. Then, the similarity score is used to determine if the human visual intention is on the object. We compare our approach with a fixation-based method and HitScan with a run length in the scenario of selecting daily objects by gaze. Our experimental results indicate that the GazeEMD approach has higher accuracy and is more robust to noises than the other approaches. Hence, the users can lessen cognitive load by using our approach in the real-world HRI scenario.

Peer Sharing Facilitates the Effect of Inquiry-based Projects on Science Learning

2010 ◽  
Vol 72 (1) ◽  
pp. 24-29 ◽  
Author(s):  
Hui-Min Chung ◽  
Kristina Jackson Behan
Keyword(s):  
Popular Culture ◽  
Real World ◽  
Scientific Inquiry ◽  
Science Learning ◽  
Group Learning ◽  
Authentic Assessment ◽  
The Other ◽  
Learning Activity ◽  
Millennial Students ◽  
Inquiry Based Learning

Authentic assessment exercises are similar to real-world tasks that would be expected by a professional. An authentic assessment in combination with an inquiry-based learning activity enhances students' learning and rehearses them for their future roles, whether as scientists or as informed citizens. Over a period of 2 years, we experimented with two inquiry-based projects; one had traditional scientific inquiry characteristics, and the other used popular culture as the medium of inquiry. We found that activities that incorporated group learning motivated students and sharpened their abilities to apply and communicate their knowledge of science. We also discovered that incorporating popular culture provided ““Millennial”” students with a refreshing view of science learning and increased their appetites to explore and elaborate on science.

ERGUN ÖZBUDUN, Contemporary Turkish Politics: Challenges to Democratic Consolidation (Boulder, Colo.: Lynne Rienner, 2000). Pp. 181. $49.95 cloth.

2001 ◽  
Vol 33 (4) ◽  
pp. 657-660
Author(s):  
Frank Tachau
Keyword(s):  
Middle East ◽  
Current Literature ◽  
Real World ◽  
Democratic Consolidation ◽  
World Politics ◽  
The Other ◽  
Southern Europe ◽  
Turkish Politics ◽  
Political Studies

Based on Professor Özbudun's lectures at Bilkent University, this book is at once compact, highly readable, and very insightful. Unlike much current literature on Turkey, the analysis is set in a broad and informed comparative context. Turkey, the author points out, has been left out of comparative political studies, particularly those encompassing the Middle East and southern Europe, in which arguably it could (or should) have been included. Scholarly neglect thus reflects real-world politics: Turkey falls between two worlds, one of which it once largely controlled, the other to which it currently aspires to belong. This lacuna is one of the factors that persuaded Özbudun to publish this volume.

scholarly journals An Optimal and Stable Algorithm for Clustering Numerical Data

Algorithms ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 197
Author(s):  
Ali Seman ◽  
Azizian Mohd Sapawi
Keyword(s):  
Standard Deviation ◽  
Real World ◽  
Clustering Algorithm ◽  
Numerical Data ◽  
Zero Point ◽  
The Other ◽  
Suitable Alternative ◽  
Stable Algorithm ◽  
Real World Applications

In the conventional k-means framework, seeding is the first step toward optimization before the objects are clustered. In random seeding, two main issues arise: the clustering results may be less than optimal and different clustering results may be obtained for every run. In real-world applications, optimal and stable clustering is highly desirable. This report introduces a new clustering algorithm called the zero k-approximate modal haplotype (Zk-AMH) algorithm that uses a simple and novel seeding mechanism known as zero-point multidimensional spaces. The Zk-AMH provides cluster optimality and stability, therefore resolving the aforementioned issues. Notably, the Zk-AMH algorithm yielded identical mean scores to maximum, and minimum scores in 100 runs, producing zero standard deviation to show its stability. Additionally, when the Zk-AMH algorithm was applied to eight datasets, it achieved the highest mean scores for four datasets, produced an approximately equal score for one dataset, and yielded marginally lower scores for the other three datasets. With its optimality and stability, the Zk-AMH algorithm could be a suitable alternative for developing future clustering tools.

scholarly journals Copyful Streaming String Transducers

2021 ◽  
Vol 178 (1-2) ◽  
pp. 59-76
Author(s):  
Emmanuel Filiot ◽  
Pierre-Alain Reynier
Keyword(s):  
Polynomial Time ◽  
Equivalence Problem ◽  
Expressive Power ◽  
The Other ◽  
Finite State Automata ◽  
Finite State ◽  
Variable Content ◽  
Deterministic Automata ◽  
Intermediate Output ◽  
Linear Manner

Copyless streaming string transducers (copyless SST) have been introduced by R. Alur and P. Černý in 2010 as a one-way deterministic automata model to define transductions of finite strings. Copyless SST extend deterministic finite state automata with a set of variables in which to store intermediate output strings, and those variables can be combined and updated all along the run, in a linear manner, i.e., no variable content can be copied on transitions. It is known that copyless SST capture exactly the class of MSO-definable string-to-string transductions, and are as expressive as deterministic two-way transducers. They enjoy good algorithmic properties. Most notably, they have decidable equivalence problem (in PSpace). On the other hand, HDT0L systems have been introduced for a while, the most prominent result being the decidability of the equivalence problem. In this paper, we propose a semantics of HDT0L systems in terms of transductions, and use it to study the class of deterministic copyful SST. Our contributions are as follows: (i)HDT0L systems and total deterministic copyful SST have the same expressive power, (ii)the equivalence problem for deterministic copyful SST and the equivalence problem for HDT0L systems are inter-reducible, in quadratic time. As a consequence, equivalence of deterministic SST is decidable, (iii)the functionality of non-deterministic copyful SST is decidable, (iv)determining whether a non-deterministic copyful SST can be transformed into an equivalent non-deterministic copyless SST is decidable in polynomial time.

Sequential Preference Revelation in Incomplete Information Settings

2021 ◽  
Vol 13 (1) ◽  
pp. 116-147
Author(s):  
James Schummer ◽  
Rodrigo A. Velez
Keyword(s):  
Incomplete Information ◽  
Real World ◽  
Private Information ◽  
Allocation Rules ◽  
Is Strategy ◽  
Strategy Proof ◽  
Simultaneous Move

Strategy-proof allocation rules incentivize truthfulness in simultaneous move games, but real world mechanisms sometimes elicit preferences sequentially. Surprisingly, even when the underlying rule is strategy-proof and nonbossy, sequential elicitation can yield equilibria where agents have a strict incentive to be untruthful. This occurs only under incomplete information, when an agent anticipates that truthful reporting would signal false private information about others’ preferences. We provide conditions ruling out this phenomenon, guaranteeing all equilibrium outcomes to be welfare-equivalent to truthful ones. (JEL C73, D45, D82, D83)

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