Stephanie Milani

43 papers A* 8A 1C 1Journal 25Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	The PokeAgent Challenge: Competitive and Long-Context Learning at Scale. CoRR Seth Karten, Jake Grigsby, Tersoo Upaa Jr, Junik Bae, Seonghun Hong, Hyunyoung Jeong, Jaeyoon Jung, Kun Kerdthaisong, Gyungbo Kim, Hyeokgi Kim, Yujin Kim, Eunju Kwon, Dongyu Liu, Patrick Mariglia, Sangyeon Park, Benedikt Schink, Xianwei Shi, Anthony Sistilli, Joseph Twin, Arian Urdu, Matin Urdu, Qiao Wang, Ling Wu, Wenli Zhang, Kunsheng Zhou, Stephanie Milani, Kiran Vodrahalli, Amy Zhang, Fei Fang, Yuke Zhu, Chi Jin
2025	A*	`conf`	LICORICE: Label-Efficient Concept-Based Interpretable Reinforcement Learning. ICLR Zhuorui Ye, Stephanie Milani, Geoffrey J. Gordon, Fei Fang
2025	J	`jnl`	Making Teams and Influencing Agents: Efficiently Coordinating Decision Trees for Interpretable Multi-Agent Reinforcement Learning. CoRR Rex Chen, Stephanie Milani, Zhicheng Zhang, Norman M. Sadeh, Fei Fang
2024	J	`jnl`	Concept-Based Interpretable Reinforcement Learning with Limited to No Human Labels. CoRR Zhuorui Ye, Stephanie Milani, Geoffrey J. Gordon, Fei Fang
2024	J	`jnl`	Explainable Reinforcement Learning: A Survey and Comparative Review. ACM Comput. Surv. Stephanie Milani, Nicholay Topin, Manuela Veloso, Fei Fang
2024	J	`jnl`	Interpretability in Action: Exploratory Analysis of VPT, a Minecraft Agent. CoRR Karolis Jucys, George Adamopoulos, Mehrab Hamidi, Stephanie Milani, Mohammad Reza Samsami, Artem Zholus, Sonia Joseph, Blake A. Richards, Irina Rish, Özgür Simsek
2024	A	`conf`	MABL: Bi-Level Latent-Variable World Model for Sample-Efficient Multi-Agent Reinforcement Learning. AAMAS Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran
2024	J	`jnl`	PATIENT-Ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals. CoRR 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
2024	A*	`conf`	PATIENT-ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals. EMNLP 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
2024	J	`jnl`	Unifying Interpretability and Explainability for Alzheimer's Disease Progression Prediction. CoRR Raja Farrukh Ali, Stephanie Milani, John Woods, Emmanuel Adenij, Ayesha Farooq, Clayton Mansel, Jeffrey Burns, William H. Hsu
2024	A*	`conf`	When is Transfer Learning Possible? ICML My Phan, Kianté Brantley, Stephanie Milani, Soroush Mehri, Gokul Swamy, Geoffrey J. Gordon
2023	A*	`conf`	BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks. NeurIPS Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Rohin Shah
2023	J	`jnl`	BEDD: The MineRL BASALT Evaluation and Demonstrations Dataset for Training and Benchmarking Agents that Solve Fuzzy Tasks. CoRR Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Rohin Shah
2023	J	`jnl`	Bi-level Latent Variable Model for Sample-Efficient Multi-Agent Reinforcement Learning. CoRR Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran
2023	A*	`conf`	Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games. CHI Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
2023	J	`jnl`	Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games. CoRR Stephanie Milani, Arthur Juliani, Ida Momennejad, Raluca Georgescu, Jaroslaw Rzepecki, Alison Shaw, Gavin Costello, Fei Fang, Sam Devlin, Katja Hofmann
2023	J	`jnl`	Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. CoRR 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
2022	J	`jnl`	A Survey of Explainable Reinforcement Learning. CoRR Stephanie Milani, Nicholay Topin, Manuela Veloso, Fei Fang
2022	—	`conf`	How Humans Perceive Human-like Behavior in Video Game Navigation. CHI Extended Abstracts 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
2022	J	`jnl`	MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning. CoRR Stephanie Milani, Zhicheng Zhang, Nicholay Topin, Zheyuan Ryan Shi, Charles A. Kamhoua, Evangelos E. Papalexakis, Fei Fang
2022	—	`conf`	MAVIPER: Learning Decision Tree Policies for Interpretable Multi-agent Reinforcement Learning. ECML/PKDD (4) Stephanie Milani, Zhicheng Zhang, Nicholay Topin, Zheyuan Ryan Shi, Charles A. Kamhoua, Evangelos E. Papalexakis, Fei Fang
2022	J	`jnl`	MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned. CoRR 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
2022	J	`jnl`	Retrospective on the 2021 BASALT Competition on Learning from Human Feedback. CoRR 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
2022	J	`jnl`	Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers. CoRR Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin
2022	J	`jnl`	UniMASK: Unified Inference in Sequential Decision Problems. CoRR Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin
2022	A*	`conf`	Uni[MASK]: Unified Inference in Sequential Decision Problems. NeurIPS Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin
2021	A*	`conf`	Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods. AAAI Nicholay Topin, Stephanie Milani, Fei Fang, Manuela Veloso
2021	J	`jnl`	Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods. CoRR Nicholay Topin, Stephanie Milani, Fei Fang, Manuela Veloso
2021	—	`conf`	MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned. NeurIPS (Competition and Demos) 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
2021	—	`conf`	Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback. NeurIPS (Competition and Demos) 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
2021	J	`jnl`	The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors. CoRR 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
2021	J	`jnl`	The MineRL BASALT Competition on Learning from Human Feedback. CoRR 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
2021	—	`conf`	Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. NeurIPS (Competition and Demos) 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
2021	J	`jnl`	Towards robust and domain agnostic reinforcement learning competitions. CoRR 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
2020	J	`jnl`	Guaranteeing Reproducibility in Deep Learning Competitions. CoRR Brandon Houghton, Stephanie Milani, Nicholay Topin, William H. Guss, Katja Hofmann, Diego Perez Liebana, Manuela Veloso, Ruslan Salakhutdinov
2020	—	`conf`	Harnessing the Power of Deception in Attack Graph-Based Security Games. GameSec Stephanie Milani, Weiran Shen, Kevin S. Chan, Sridhar Venkatesan, Nandi O. Leslie, Charles A. Kamhoua, Fei Fang
2020	A*	`conf`	Planning with Abstract Learned Models While Learning Transferable Subtasks. AAAI John Winder, Stephanie Milani, Matthew Landen, Erebus Oh, Shane Parr, Shawn Squire, Marie desJardins, Cynthia Matuszek
2020	J	`jnl`	Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning. CoRR Stephanie Milani, Nicholay Topin, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Keisuke Nakata, Oriol Vinyals, Noboru Sean Kuno
2020	—	`conf`	Towards robust and domain agnostic reinforcement learning competitions: MineRL 2020. NeurIPS (Competition and Demos) 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
2019	C	`conf`	Perceptions of Domestic Robots' Normative Behavior Across Cultures. AIES Huao Li, Stephanie Milani, Vigneshram Krishnamoorthy, Michael Lewis, Katia P. Sycara
2019	J	`jnl`	Planning with Abstract Learned Models While Learning Transferable Subtasks. CoRR John Winder, Stephanie Milani, Matthew Landen, Erebus Oh, Shane Parr, Shawn Squire, Marie desJardins, Cynthia Matuszek
2019	—	`conf`	Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning. NeurIPS (Competition and Demos) Stephanie Milani, Nicholay Topin, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Keisuke Nakata, Oriol Vinyals, Noboru Sean Kuno
2019	J	`jnl`	The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors. CoRR 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