Machine Intelligence through Decision-making and Interaction

Offline Action-Free Learning of Ex-BMDPs by Comparing Diverse Datasets
Alexander Levine, Peter Stone, Amy Zhang
RLC 2025

Fast Adaptation with Behavioral Foundation Models
Harshit Sikchi, Andrea Tirinzoni, Ahmed Touati, Yingchen Xu, Anssi Kanervisto, Scott Niekum, Amy Zhang, Alessandro Lazaric, Matteo Pirotta
RLC 2025

Proto Successor Measure: Representing the Behavior Space of an RL Agent
Siddhant Agarwal, Harshit Sikchi, Peter Stone, Amy Zhang
ICML 2025 (to appear) / arxiv

CRESTE: Scalable Mapless Navigation with Internet Scale Priors and Counterfactual Guidance
Arthur Zhang, Harshit Sikchi, Amy Zhang, Joydeep Biswas
RSS 2025 / project page

An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning
Haoran Xu, Shuozhe Li, Harshit Sikchi, Scott Niekum, Amy Zhang
ICLR 2025 / project page

Learning a Fast Mixing Exogenous Block MDP using a Single Trajectory
Alexander Levine, Peter Stone, Amy Zhang
ICLR 2025 / code

EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation
Carl Qi, Dan Haramati, Tal Daniel, Aviv Tamar, Amy Zhang
ICLR 2025 / project page

RL Zero: Zero-Shot Language to Behaviors without any Supervision
Harshit Sikchi, Siddhant Agarwal, Pranaya Jajoo, Samyak Parajuli, Caleb Chuck, Max Rudolph, Peter Stone, Amy Zhang, Scott Niekum
arxiv / ICLR 2025 Robot Learning Workshop / project page

Augmented Conditioning Is Enough For Effective Training Image Generation
Jiahui Chen, Amy Zhang, Adriana Romero-Soriano
arxiv / ICLR 2025 SynthData Workshop

Reevaluating Policy Gradient Methods for Imperfect-Information Games
Max Rudolph, Nathan Lichtle, Sobhan Mohammadpour, Alexndre Bayen, J. Zico Kolter, Amy Zhang, Eugene Vinitsky, Sam Sokota
arxiv / project page

Multistep Inverse Is Not All You Need
Alexander Levine, Peter Stone, Amy Zhang
RLC 2024 / code

Learning Action-based Representations Using Invariance
Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky, Scott Niekum, Amy Zhang
RLC 2024 / project page

A Dual Approach to Imitation Learning from Observations with Offline Datasets
Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum
CoRL 2024 / project page

Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning
Liyuan Mao*, Haoran Xu*, Weinan Zhang, Xianyuan Zhan, Amy Zhang
NeurIPS 2024 / project page

AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers
Jake Grigsby, Justin Sasek, Samyak Parajuli, Daniel Adebi, Amy Zhang, Yuke Zhu
NeurIPS 2024 / project page

SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions
Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone
NeurIPS 2024 / project page

Score Models for Offline Goal-Conditioned Reinforcement Learning
Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum
ICLR 2024 / project page

Dual RL: Unification and new methods for reinforcement and imitation learning
Harshit Sikchi, Qinqing Zheng, Amy Zhang, Scott Niekum
ICLR 2024 / project page

Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning
Caleb Chuck, Carl Qi, Michael J Munje, Shuozhe Li, Max Rudolph, Chang Shi, Siddhant Agarwal, Harshit Sikchi, Abhinav Peri, Sarthak Dayal, Evan Kuo, Kavan Mehta, Anthony Wang, Peter Stone, Amy Zhang, Scott Niekum
arxiv / ICRA 2024 Workshop on Manipulation Skills / project page

Automated Discovery of Functional Actual Causes in Complex Environments
Caleb Chuck, Sankaran Vaidyanathan, Stephen Giguere, Amy Zhang, David Jensen, Scott Niekum
arxiv / project page

f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergences
Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang
NeurIPS 2023 / project page