200 citations · 260 across the 20 of their papers we have counts for
6 papers · 1 filter
Integrated Task Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery
Zhe Chen, Javier Alonso-Mora, Xiaoshan Bai +2
Multi-agent Pickup and Delivery (MAPD) is a challenging industrial problem where a team of robots is tasked with transporting a set of tasks, each from an initial location and each…
Planning with Learned Binarized Neural Networks Benchmarks for MaxSAT Evaluation 2021
Buser Say, Scott Sanner, Jo Devriendt +2
This document provides a brief introduction to learned automated planning problem where the state transition function is in the form of a binarized neural network (BNN), presents a…
Assertion-Based Approaches to Auditing Complex Elections, with Application to Party-List Proportional Elections
Michelle Blom, Jurlind Budurushi, Ronald L. Rivest +4
Risk-limiting audits (RLAs), an ingredient in evidence-based elections, are increasingly common. They are a rigorous statistical means of ensuring that electoral results are correc…
Pairwise Symmetry Reasoning for Multi-Agent Path Finding Search
Jiaoyang Li, Daniel Harabor, Peter J. Stuckey +1
Multi-Agent Path Finding (MAPF) is a challenging combinatorial problem that asks us to plan collision-free paths for a team of cooperative agents. In this work, we show that one of…
A Scalable Two Stage Approach to Computing Optimal Decision Sets
Alexey Ignatiev, Edward Lam, Peter J. Stuckey +1
Machine learning (ML) is ubiquitous in modern life. Since it is being deployed in technologies that affect our privacy and safety, it is often crucial to understand the reasoning b…
Symmetry Breaking for k-Robust Multi-Agent Path Finding
Zhe Chen, Daniel Harabor, Jiaoyang Li +1
During Multi-Agent Path Finding (MAPF) problems, agents can be delayed by unexpected events. To address such situations recent work describes k-Robust Conflict-BasedSearch (k-CBS):…