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Found 51 papers, 1 papers with code
Nash Welfare and Facility Location
We consider the problem of locating a facility to serve a set of agents located along a line.
Mechanisms that play a game, not toss a coin
We propose a number of novel derandomized mechanisms for these six domains with good normative properties.
Incentives to Offer Algorithmic Recourse
Due to the importance of artificial intelligence (AI) in a variety of high-stakes decisions, such as loan approval, job hiring, and criminal bail, researchers in Explainable AI (XAI) have developed algorithms to provide users with recourse for an unfavorable outcome.
Proportional Fairness in Obnoxious Facility Location
On the other hand, in the randomized setting, we identify proportionally fair and strategyproof mechanisms that give an expected welfare within a constant factor of the optimal welfare.
Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report
In September 2021, the "One Hundred Year Study on Artificial Intelligence" project (AI100) issued the second report of its planned long-term periodic assessment of artificial intelligence (AI) and its impact on society.
Manipulation and Peer Mechanisms: A Survey
In peer mechanisms, the competitors for a prize also determine who wins.
Random Rank: The One and Only Strategyproof and Proportionally Fair Randomized Facility Location Mechanism
Proportionality is an attractive fairness concept that has been applied to a range of problems including the facility location problem, a classic problem in social choice.
What Type of Explanation Do Rejected Job Applicants Want? Implications for Explainable AI
Rejected job applicants seldom receive explanations from employers.
Fairness Amidst Non-IID Graph Data: Current Achievements and Future Directions
The importance of understanding and correcting algorithmic bias in machine learning (ML) has led to an increase in research on fairness in ML, which typically assumes that the underlying data is independent and identically distributed (IID).
Strategyproof and Proportionally Fair Facility Location
We show that imposing strategyproofness renders many of the axioms to be equivalent: the family of mechanisms that satisfy proportionality, unanimity, and strategyproofness is equivalent to the family of mechanisms that satisfy UFS and strategyproofness, which, in turn, is equivalent to the family of mechanisms that satisfy PF and strategyproofness.
Strategy Proof Mechanisms for Facility Location with Capacity Limits
An important feature of many real world facility location problems are capacity limits on the facilities.
Strategy Proof Mechanisms for Facility Location in Euclidean and Manhattan Space
We study the impact on mechanisms for facility location of moving from one dimension to two (or more) dimensions and Euclidean or Manhattan distances.
Strategy Proof Mechanisms for Facility Location at Limited Locations
Facility location problems often permit facilities to be located at any position.
Adventures in Mathematical Reasoning
"Mathematics is not a careful march down a well-cleared highway, but a journey into a strange wilderness, where the explorers often get lost.
On the Complexity of Breaking Symmetry
We can break symmetry by eliminating solutions within a symmetry class that are not least in the lexicographical ordering.
Fair Division: The Computer Scientist's Perspective
I survey recent progress on a classic and challenging problem in social choice: the fair division of indivisible items.
In Search for a SAT-friendly Binarized Neural Network Architecture
Analyzing the behavior of neural networks is one of the most pressing challenges in deep learning.
A Pebble in the AI Race
Bhutan is sometimes described as \a pebble between two boulders", a small country caught between the two most populous nations on earth: India and China.
Partial Queries for Constraint Acquisition
Learning constraint networks is known to require a number of membership queries exponential in the number of variables.
From Matching with Diversity Constraints to Matching with Regional Quotas
In this paper, we present a polynomial-time reduction to transform an instance of (1) to an instance of (2) and we show how the feasibility and stability of corresponding matchings are preserved under the reduction.
Greedy Algorithms for Fair Division of Mixed Manna
For example, we show that maximizing the Nash welfare with mixed manna (or minimizing the disutility Nash welfare) does not ensure an EF1 allocation whereas with goods and the Nash welfare it does.
Facility Location Problem with Capacity Constraints: Algorithmic and Mechanism Design Perspectives
From the algorithmic perspective, we prove that the corresponding optimization problem, where the goal is to locate facilities to minimize either the total cost to all agents or the maximum cost of any agent is NP-hard.
Online Fair Division: A Survey
We survey a burgeoning and promising new research area that considers the online nature of many practical fair division problems.
A Commentary on "Breaking Row and Column Symmetries in Matrix Models"
The CP 2002 paper entitled "Breaking Row and Column Symmetries in Matrix Models" by Flener et al. (https://link. springer. com/chapter/10. 1007%2F3-540-46135-3_31) describes some of the first work for identifying and analyzing row and column symmetry in matrix models and for efficiently and effectively dealing with such symmetry using static symmetry-breaking ordering constraints.
CSPLib: Twenty Years On
In 1999, we introduced CSPLib, a benchmark library for the constraints community.
SAT vs CSP: a commentary
In 2000, I published a relatively comprehensive study of mappings between propositional satisfiability (SAT) and constraint satisfaction problems (CSPs) [Wal00].
Deceased Organ Matching in Australia
Despite efforts to increase the supply of organs from living donors, most kidney transplants performed in Australia still come from deceased donors.
Verifying Properties of Binarized Deep Neural Networks
To the best of our knowledge, this is the first work on verifying properties of deep neural networks using an exact Boolean encoding of the network.
Expert and Non-Expert Opinion about Technological Unemployment
To look into this issue in more depth, we surveyed experts in Robotics and AI about the risk, and compared their views with those of non-experts.
The Conference Paper Assignment Problem: Using Order Weighted Averages to Assign Indivisible Goods
Motivated by the common academic problem of allocating papers to referees for conference reviewing we propose a novel mechanism for solving the assignment problem when we have a two sided matching problem with preferences from one side (the agents/reviewers) over the other side (the objects/papers) and both sides have capacity constraints.
Ethical Considerations in Artificial Intelligence Courses
The recent surge in interest in ethics in artificial intelligence may leave many educators wondering how to address moral, ethical, and philosophical issues in their AI courses.
Empirical Evaluation of Real World Tournaments
Computational Social Choice (ComSoc) is a rapidly developing field at the intersection of computer science, economics, social choice, and political science.
Interdependent Scheduling Games
We propose a model of interdependent scheduling games in which each player controls a set of services that they schedule independently.
Strategyproof Peer Selection using Randomization, Partitioning, and Apportionment
Peer reviews, evaluations, and selections are a fundamental aspect of modern science.
The Singularity May Never Be Near
There is both much optimism and pessimism around artificial intelligence (AI) today.
Welfare of Sequential Allocation Mechanisms for Indivisible Goods
Sequential allocation is a simple and attractive mechanism for the allocation of indivisible goods.
Turing's Red Flag
Sometime in the future we will have to deal with the impact of AI's being mistaken for humans.
Online Fair Division: analysing a Food Bank problem
We study an online model of fair division designed to capture features of a real world charity problem.
Possible and Necessary Allocations via Sequential Mechanisms
We focus on possible and necessary allocation problems, checking whether allocations of a given form occur in some or all mechanisms for several commonly used classes of sequential allocation mechanisms.
A Study of Proxies for Shapley Allocations of Transport Costs
We propose and evaluate a number of solutions to the problem of calculating the cost to serve each location in a single-vehicle transport setting.
Computational Aspects of Multi-Winner Approval Voting
We study computational aspects of three prominent voting rules that use approval ballots to elect multiple winners.
Allocation in Practice
In the first, we have been working with FoodBank Local, a social startup working in collaboration with food bank charities around the world to optimise the logistics of collecting and distributing donated food.
The Computational Impact of Partial Votes on Strategic Voting
These methods modify scoring rules (like the Borda count), elimination style rules (like single transferable vote) and rules based on the tournament graph (like Copeland) respectively.
The PeerRank Method for Peer Assessment
Since the grade of an agent is a measure of their ability to grade correctly, the PeerRank method weights grades by the grades of the grading agent.
Fair assignment of indivisible objects under ordinal preferences
The computational complexity of checking whether a fair assignment exists is studied for these fairness notions.
Breaking Symmetry with Different Orderings
We can break symmetry by eliminating solutions within each symmetry class.
How Hard Is It to Control an Election by Breaking Ties?
Indeed, we prove that it can be NP-hard to control an election by breaking ties even with a two-stage voting rule.
A Social Welfare Optimal Sequential Allocation Procedure
We consider a simple sequential allocation procedure for sharing indivisible items between agents in which agents take turns to pick items.
Three Generalizations of the FOCUS Constraint
The FOCUS constraint expresses the notion that solutions are concentrated.
Coalitional Manipulation for Schulze's Rule
Schulze's rule is used in the elections of a large number of organizations including Wikimedia and Debian.
