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08/22/2023
Traffic Flow Optimisation for Lifelong Multi-Agent Path Finding
Multi-Agent Path Finding (MAPF) is a fundamental problem in robotics tha...
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08/11/2023
The divergence time of protein structures modelled by Markov matrices and its relation to the divergence of sequences
A complete time-parameterized statistical model quantifying the divergen...
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07/20/2023
Adaptively Weighted Audits of Instant-Runoff Voting Elections: AWAIRE
An election audit is risk-limiting if the audit limits (to a pre-specifi...
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07/17/2023
Lifted Sequential Planning with Lazy Constraint Generation Solvers
This paper studies the possibilities made open by the use of Lazy Clause...
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07/07/2023
On Formal Feature Attribution and Its Approximation
Recent years have witnessed the widespread use of artificial intelligenc...
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06/28/2023
Reducing Redundant Work in Jump Point Search
JPS (Jump Point Search) is a state-of-the-art optimal algorithm for onli...
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06/10/2023
Scalable Rail Planning and Replanning with Soft Deadlines
The Flatland Challenge, which was first held in 2019 and reported in Neu...
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05/15/2023
Tracking Progress in Multi-Agent Path Finding
Multi-Agent Path Finding (MAPF) is an important core problem for many ne...
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03/18/2023
Risk-Limiting Audits for Condorcet Elections
Elections where electors rank the candidates (or a subset of the candida...
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03/17/2023
ChameleonIDE: Untangling Type Errors Through Interactive Visualization and Exploration
Dynamically typed programming languages are popular in education and the...
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09/08/2022
Ballot-Polling Audits of Instant-Runoff Voting Elections with a Dirichlet-Tree Model
Instant-runoff voting (IRV) is used in several countries around the worl...
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07/06/2022
Multi-Target Search in Euclidean Space with Ray Shooting (Full Version)
The Euclidean shortest path problem (ESPP) is a well studied problem wit...
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06/29/2022
Auditing Ranked Voting Elections with Dirichlet-Tree Models: First Steps
Ranked voting systems, such as instant-runoff voting (IRV) and single tr...
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06/20/2022
Eliminating The Impossible, Whatever Remains Must Be True
The rise of AI methods to make predictions and decisions has led to a pr...
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05/29/2022
Assessing the accuracy of the Australian Senate count: Key steps for a rigorous and transparent audit
This paper explains the main principles and some of the technical detail...
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12/18/2021
A First Approach to Risk-Limiting Audits for Single Transferable Vote Elections
Risk-limiting audits (RLAs) are an increasingly important method for che...
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10/28/2021
Integrated Task Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery
Multi-agent Pickup and Delivery (MAPD) is a challenging industrial probl...
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08/06/2021
Transformation-Enabled Precondition Inference
Precondition inference is a non-trivial problem with important applicati...
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08/02/2021
Planning with Learned Binarized Neural Networks Benchmarks for MaxSAT Evaluation 2021
This document provides a brief introduction to learned automated plannin...
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07/25/2021
Assertion-based Approaches to Auditing Complex Elections, with application to party-list proportional elections
Risk-limiting audits (RLAs), an ingredient in evidence-based elections, ...
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03/12/2021
Pairwise Symmetry Reasoning for Multi-Agent Path Finding Search
Multi-Agent Path Finding (MAPF) is a challenging combinatorial problem t...
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02/17/2021
Symmetry Breaking for k-Robust Multi-Agent Path Finding
During Multi-Agent Path Finding (MAPF) problems, agents can be delayed b...
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02/17/2021
Auditing Hamiltonian Elections
Presidential primaries are a critical part of the United States Presiden...
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02/03/2021
A Scalable Two Stage Approach to Computing Optimal Decision Sets
Machine learning (ML) is ubiquitous in modern life. Since it is being de...
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12/04/2020
Divide and Learn: A Divide and Conquer Approach for Predict+Optimize
The predict+optimize problem combines machine learning ofproblem coeffic...
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10/19/2020
Optimal Decision Lists using SAT
Decision lists are one of the most easily explainable machine learning m...
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09/15/2020
Optimal Decision Trees for Nonlinear Metrics
Nonlinear metrics, such as the F1-score, Matthews correlation coefficien...
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07/29/2020
Computing Optimal Decision Sets with SAT
As machine learning is increasingly used to help make decisions, there i...
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07/24/2020
MurTree: Optimal Classification Trees via Dynamic Programming and Search
Decision tree learning is a widely used approach in machine learning, fa...
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07/02/2020
Random errors are not politically neutral
Errors are inevitable in the implementation of any complex process. Here...
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04/01/2020
You can do RLAs for IRV
The City and County of San Francisco, CA, has used Instant Runoff Voting...
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11/22/2019
Smart Predict-and-Optimize for Hard Combinatorial Optimization Problems
Combinatorial optimization assumes that all parameters of the optimizati...
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03/20/2019
Risk-Limiting Audits for IRV Elections
Risk-limiting post election audits guarantee a high probability of corre...
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12/21/2018
Solution Dominance over Constraint Satisfaction Problems
Constraint Satisfaction Problems (CSPs) typically have many solutions th...
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12/15/2018
Searching with Consistent Prioritization for Multi-Agent Path Finding
We study prioritized planning for Multi-Agent Path Finding (MAPF). Exist...
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11/16/2018
Precondition Inference via Partitioning of Initial States
Precondition inference is a non-trivial task with several applications i...
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08/02/2018
Pre-proceedings of the 28th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2018)
This volume constitutes the pre-proceedings of the 28th International Sy...
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04/17/2018
An iterative approach to precondition inference using constrained Horn clauses
We present a method for automatic inference of conditions on the initial...
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08/25/2015
Unsatisfiable Cores and Lower Bounding for Constraint Programming
Constraint Programming (CP) solvers typically tackle optimization proble...
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08/20/2015
Efficient Computation of Exact IRV Margins
The margin of victory is easy to compute for many election schemes but d...
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06/19/2013
Structure Based Extended Resolution for Constraint Programming
Nogood learning is a powerful approach to reducing search in Constraint ...
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05/08/2013
Unsatisfiable Cores for Constraint Programming
Constraint Programming (CP) solvers typically tackle optimization proble...
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08/15/2012
Explaining Time-Table-Edge-Finding Propagation for the Cumulative Resource Constraint
Cumulative resource constraints can model scarce resources in scheduling...
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03/06/2012
Search Combinators
The ability to model search in a constraint solver can be an essential a...
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04/24/2011
Boolean Equi-propagation for Optimized SAT Encoding
We present an approach to propagation based solving, Boolean equi-propag...
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09/02/2010