Stephanie Milani

According to our database, Stephanie Milani authored at least 33 papers between 2019 and 2024.

Collaborative distances:

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

2024

Explainable Reinforcement Learning: A Survey and Comparative Review.

Stephanie Milani, Nicholay Topin, Manuela Veloso, Fei Fang

ACM Comput. Surv., July, 2024

Concept-Based Interpretable Reinforcement Learning with Limited to No Human Labels.

Zhuorui Ye, Stephanie Milani, Geoffrey J. Gordon, Fei Fang

CoRR, 2024

Interpretability in Action: Exploratory Analysis of VPT, a Minecraft Agent.

Karolis Jucys, George Adamopoulos, Mehrab Hamidi, Stephanie Milani, Mohammad Reza Samsami, Artem Zholus, Sonia Joseph, Blake A. Richards, Irina Rish, Özgür Simsek

CoRR, 2024

Unifying Interpretability and Explainability for Alzheimer's Disease Progression Prediction.

Raja Farrukh Ali, Stephanie Milani, John Woods, Emmanuel Adenij, Ayesha Farooq, Clayton Mansel, Jeffrey Burns, William H. Hsu

CoRR, 2024

PATIENT-Ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals.

Ruiyi Wang, Stephanie Milani, Jamie C. Chiu, Shaun M. Eack, Travis Labrum, Samuel M. Murphy, Nev Jones, Kate Hardy, Hong Shen, Fei Fang, Zhiyu Zoey Chen

CoRR, 2024

When is Transfer Learning Possible?

My Phan, Kianté Brantley, Stephanie Milani, Soroush Mehri, Gokul Swamy, Geoffrey J. Gordon

Proceedings of the Forty-first International Conference on Machine Learning, 2024

PATIENT-ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals.

Ruiyi Wang, Stephanie Milani, Jamie C. Chiu, Jiayin Zhi, Shaun M. Eack, Travis Labrum, Samuel M. Murphy, Nev Jones, Kate Hardy, Hong Shen, Fei Fang, Zhiyu Chen

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

MABL: Bi-Level Latent-Variable World Model for Sample-Efficient Multi-Agent Reinforcement Learning.

Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran

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

2023

Bi-level Latent Variable Model for Sample-Efficient Multi-Agent Reinforcement Learning.

Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran

CoRR, 2023

Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition.

Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Sharada P. Mohanty, Byron Galbraith, Ke Chen, Yan Song, Tianze Zhou, Bingquan Yu, He Liu, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Ellen R. Novoseller, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins, Josh Miller, Rohin Shah

CoRR, 2023

BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks.

Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Rohin Shah

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games.

Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

2022

UniMASK: Unified Inference in Sequential Decision Problems.

Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin

CoRR, 2022

Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers.

Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin

CoRR, 2022

Retrospective on the 2021 BASALT Competition on Learning from Human Feedback.

Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Jun Shern Chan, Daniel del Castillo, Tom Lieberum

CoRR, 2022

A Survey of Explainable Reinforcement Learning.

Stephanie Milani, Nicholay Topin, Manuela Veloso, Fei Fang

CoRR, 2022

MAVIPER: Learning Decision Tree Policies for Interpretable Multi-agent Reinforcement Learning.

Stephanie Milani, Zhicheng Zhang, Nicholay Topin, Zheyuan Ryan Shi, Charles A. Kamhoua, Evangelos E. Papalexakis, Fei Fang

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Uni[MASK]: Unified Inference in Sequential Decision Problems.

Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin

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

How Humans Perceive Human-like Behavior in Video Game Navigation.

Evelyn Zuniga, Stephanie Milani, Guy Leroy, Jaroslaw Rzepecki, Raluca Georgescu, Ida Momennejad, David Bignell, Mingfei Sun, Alison Shaw, Gavin Costello, Mikhail Jacob, Sam Devlin, Katja Hofmann

Proceedings of the CHI '22: CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA, 29 April 2022, 2022

2021

The MineRL BASALT Competition on Learning from Human Feedback.

Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca D. Dragan

CoRR, 2021

Towards robust and domain agnostic reinforcement learning competitions.

William Hebgen Guss, Stephanie Milani, Nicholay Topin, Brandon Houghton, Sharada P. Mohanty, Andrew Melnik, Augustin Harter, Benoit Buschmaas, Bjarne Jaster, Christoph Berganski, Dennis Heitkamp, Marko Henning, Helge J. Ritter, Chengjie Wu, Xiaotian Hao, Yiming Lu, Hangyu Mao, Yihuan Mao, Chao Wang, Michal Opanowicz, Anssi Kanervisto, Yanick Schraner, Christian Scheller, Xiren Zhou, Lu Liu, Daichi Nishio, Toi Tsuneda, Karolis Ramanauskas, Gabija Juceviciute

CoRR, 2021

The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors.

William H. Guss, Mario Ynocente Castro, Sam Devlin, Brandon Houghton, Noboru Sean Kuno, Crissman Loomis, Stephanie Milani, Sharada P. Mohanty, Keisuke Nakata, Ruslan Salakhutdinov, John Schulman, Shinya Shiroshita, Nicholay Topin, Avinash Ummadisingu, Oriol Vinyals

CoRR, 2021

Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback.

Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Jun Shern Chan, Daniel del Castillo, Tom Lieberum

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition.

Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Sharada P. Mohanty, Byron Galbraith, Ke Chen, Yan Song, Tianze Zhou, Bingquan Yu, He Liu, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Lucas Cazzonelli, Cedric Kulbach, Nicholas Popovic, Marvin Schweizer, Ellen R. Novoseller, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins, Josh Miller, Rohin Shah

Proceedings of the NeurIPS 2022 Competition Track, 2021

MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned.

Anssi Kanervisto, Stephanie Milani, Karolis Ramanauskas, Nicholay Topin, Zichuan Lin, Junyou Li, Jianing Shi, Deheng Ye, Qiang Fu, Wei Yang, Weijun Hong, Zhongyue Huang, Haicheng Chen, Guangjun Zeng, Yue Lin, Vincent Micheli, Eloi Alonso, François Fleuret, Alexander Nikulin, Yury Belousov, Oleg Svidchenko, Aleksei Shpilman

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods.

Nicholay Topin, Stephanie Milani, Fei Fang, Manuela Veloso

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

2020

Guaranteeing Reproducibility in Deep Learning Competitions.

Brandon Houghton, Stephanie Milani, Nicholay Topin, William H. Guss, Katja Hofmann, Diego Perez Liebana, Manuela Veloso, Ruslan Salakhutdinov

CoRR, 2020

Towards robust and domain agnostic reinforcement learning competitions: MineRL 2020.

William Hebgen Guss, Stephanie Milani, Nicholay Topin, Brandon Houghton, Sharada P. Mohanty, Andrew Melnik, Augustin Harter, Benoit Buschmaas, Bjarne Jaster, Christoph Berganski, Dennis Heitkamp, Marko Henning, Helge J. Ritter, Chengjie Wu, Xiaotian Hao, Yiming Lu, Hangyu Mao, Yihuan Mao, Chao Wang, Michal Opanowicz, Anssi Kanervisto, Yanick Schraner, Christian Scheller, Xiren Zhou, Lu Liu, Daichi Nishio, Toi Tsuneda, Karolis Ramanauskas, Gabija Juceviciute

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

Harnessing the Power of Deception in Attack Graph-Based Security Games.

Stephanie Milani, Weiran Shen, Kevin S. Chan, Sridhar Venkatesan, Nandi O. Leslie, Charles A. Kamhoua, Fei Fang

Proceedings of the Decision and Game Theory for Security - 11th International Conference, 2020

Planning with Abstract Learned Models While Learning Transferable Subtasks.

John Winder, Stephanie Milani, Matthew Landen, Erebus Oh, Shane Parr, Shawn Squire, Marie desJardins, Cynthia Matuszek

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

2019

The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors.

William H. Guss, Cayden R. Codel, Katja Hofmann, Brandon Houghton, Noburu Kuno, Stephanie Milani, Sharada P. Mohanty, Diego Perez Liebana, Ruslan Salakhutdinov, Nicholay Topin, Manuela Veloso, Phillip Wang

CoRR, 2019

Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning.

Stephanie Milani, Nicholay Topin, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Keisuke Nakata, Oriol Vinyals, Noboru Sean Kuno

Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019

Perceptions of Domestic Robots' Normative Behavior Across Cultures.

Huao Li, Stephanie Milani, Vigneshram Krishnamoorthy, Michael Lewis, Katia P. Sycara

Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019