Andrew Perrault

According to our database, Andrew Perrault authored at least 43 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales.

Ju-Seung Byun, Andrew Perrault

CoRR, 2024

Reinforcement Learning for Fine-tuning Text-to-speech Diffusion Models.

Jingyi Chen, Ju-Seung Byun, Micha Elsner, Andrew Perrault

CoRR, 2024

The Distributional Reward Critic Architecture for Perturbed-Reward Reinforcement Learning.

Xi Chen, Zhihui Zhu, Andrew Perrault

CoRR, 2024

ARES: Alternating Reinforcement Learning and Supervised Fine-Tuning for Enhanced Multi-Modal Chain-of-Thought Reasoning Through Diverse AI Feedback.

Ju-Seung Byun, Jiyun Chun, Jihyung Kil, Andrew Perrault

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Time-Constrained Restless Multi-Armed Bandits with Applications to City Service Scheduling.

Yi Mao, Andrew Perrault

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Coevolutionary Algorithm for Building Robust Decision Trees under Minimax Regret.

Adam Zychowski, Andrew Perrault, Jacek Mandziuk

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize.

Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Reflections from the Workshop on AI-Assisted Decision Making for Conservation.

Lily Xu, Esther Rolf, Sara Beery, Joseph R. Bennett, Tanya Y. Berger-Wolf, Tanya Birch, Elizabeth Bondi-Kelly, Justin Brashares, Melissa S. Chapman, Anthony Corso, Andrew Davies, Nikhil Garg, Angela Gaylard, Robert Heilmayr, Hannah Kerner, Konstantin Klemmer, Vipin Kumar, Lester Mackey, Claire Monteleoni, Paul Moorcroft, Jonathan Palmer, Andrew Perrault, David Thau, Milind Tambe

CoRR, 2023

Bootstrapping a Conversational Guide for Colonoscopy Prep.

Pulkit Arya, Madeleine Bloomquist, Subhankar Chakraborty, Andrew Perrault, William Schuler, Eric Fosler-Lussier, Michael White

Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue, 2023

Using Reinforcement Learning for Multi-Objective Cluster-Level Optimization of Non-Pharmaceutical Interventions for Infectious Disease.

Xueqiao Peng, Jiaqi Xu, Xi Chen, Dinh Song An Nguyen, Andrew Perrault

Proceedings of the Machine Learning for Health, 2023

Monitoring and Intervening on Large Populations of Weakly Coupled Processes with Social Impact Applications.

Andrew Perrault

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Normality-Guided Distributional Reinforcement Learning for Continuous Control.

Ju-Seung Byun, Andrew Perrault

CoRR, 2022

Learning (Local) Surrogate Loss Functions for Predict-Then-Optimize Problems.

Sanket Shah, Bryan Wilder, Andrew Perrault, Milind Tambe

CoRR, 2022

Decision-Focused Learning without Decision-Making: Learning Locally Optimized Decision Losses.

Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Training Transition Policies via Distribution Matching for Complex Tasks.

Ju-Seung Byun, Andrew Perrault

Proceedings of the Tenth International Conference on Learning Representations, 2022

Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games.

Kai Wang, Lily Xu, Andrew Perrault, Michael K. Reiter, Milind Tambe

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning.

Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe

CoRR, 2021

Robust reinforcement learning under minimax regret for green security.

Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning.

Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Risk-Aware Interventions in Public Health: Planning with Restless Multi-Armed Bandits.

Aditya Mate, Andrew Perrault, Milind Tambe

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

Beyond "To Act or Not to Act": Fast Lagrangian Approaches to General Multi-Action Restless Bandits.

Jackson A. Killian, Andrew Perrault, Milind Tambe

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

Dual-Mandate Patrols: Multi-Armed Bandits for Green Security.

Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Collapsing Bandits and Their Application to Public Health Interventions.

Aditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe

CoRR, 2020

Game Theory on the Ground: The Effect of Increased Patrols on Deterring Poachers.

Lily Xu, Andrew Perrault, Andrew J. Plumptre, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Milind Tambe

CoRR, 2020

AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline.

Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe

CoRR, 2020

Artificial Intelligence for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline.

Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe

AI Mag., 2020

Robust Spatial-Temporal Incident Prediction.

Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel J. Kochenderfer, Milind Tambe, Yevgeniy Vorobeychik

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Collapsing Bandits and Their Application to Public Health Intervention.

Aditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Automatically Learning Compact Quality-aware Surrogates for Optimization Problems.

Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Scalable Game-Focused Learning of Adversary Models: Data-to-Decisions in Network Security Games.

Kai Wang, Andrew Perrault, Aditya Mate, Milind Tambe

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under Uncertainty.

Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, Milind Tambe

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning.

Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

End-to-End Game-Focused Learning of Adversary Behavior in Security Games.

Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Who and When to Screen: Multi-Round Active Screening for Recurrent Infectious Diseases Under Uncertainty.

Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Milind Tambe

CoRR, 2019

Decision-Focused Learning of Adversary Behavior in Security Games.

Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe

CoRR, 2019

Experiential Preference Elicitation for Autonomous Heating and Cooling Systems.

Andrew Perrault, Craig Boutilier

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

Developing and Coordinating Autonomous Agents for Efficient Electricity Markets.

Andrew Perrault

PhD thesis, 2018

2017

Multiple-Profile Prediction-of-Use Games.

Andrew Perrault, Craig Boutilier

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Strategy-Proofness in the Stable Matching Problem with Couples.

Andrew Perrault, Joanna Drummond, Fahiem Bacchus

Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

2015

Exploring Strategy-Proofness, Uniqueness, and Pareto Optimality for the Stable Matching Problem with Couples.

Andrew Perrault, Joanna Drummond, Fahiem Bacchus

CoRR, 2015

Approximately Stable Pricing for Coordinated Purchasing of Electricity.

Andrew Perrault, Craig Boutilier

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

SAT Is an Effective and Complete Method for Solving Stable Matching Problems with Couples.

Joanna Drummond, Andrew Perrault, Fahiem Bacchus

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014

Efficient coordinated power distribution on private infrastructure.

Andrew Perrault, Craig Boutilier

Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014