When Demonstrations Meet Generative World Models: A Maximum Likelihood
Framework for Offline Inverse Reinforcement Learning

When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning

15 February 2023

Alfredo García

Papers citing "When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning"

14 / 14 papers shown

Title
Understanding Inverse Reinforcement Learning under Overparameterization: Non-Asymptotic Analysis and Global Optimality Ruijia Zhang Siliang Zeng Chenliang Li Alfredo García Mingyi Hong 62 0 0 22 Mar 2025
Grounded Answers for Multi-agent Decision-making Problem through Generative World Model Zeyang Liu Xinrui Yang Shiguang Sun Long Qian Lipeng Wan Xingyu Chen Xuguang Lan 22 2 0 03 Oct 2024
How to Leverage Diverse Demonstrations in Offline Imitation Learning Sheng Yue Jiani Liu Xingyuan Hua Ju Ren Sen Lin Junshan Zhang Yaoxue Zhang OffRL 32 2 0 24 May 2024
Conditional Kernel Imitation Learning for Continuous State Environments Rishabh Agrawal Nathan Dahlin Rahul Jain A. Nayyar 28 0 0 24 Aug 2023
Reinforcement Learning with Human Feedback: Learning Dynamic Choices via Pessimism Zihao Li Zhuoran Yang Mengdi Wang OffRL 29 54 0 29 May 2023
Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees Siliang Zeng Chenliang Li Alfredo García Min-Fong Hong 31 42 0 04 Oct 2022
Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees Siliang Zeng Mingyi Hong Alfredo García OffRL 33 12 0 04 Oct 2022
Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning Paul Rolland Luca Viano Norman Schuerhoff Boris Nikolov V. Cevher OffRL 37 13 0 22 Sep 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 311 11,915 0 04 Mar 2022
Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage Masatoshi Uehara Wen Sun OffRL 96 144 0 13 Jul 2021
COMBO: Conservative Offline Model-Based Policy Optimization Tianhe Yu Aviral Kumar Rafael Rafailov Aravind Rajeswaran Sergey Levine Chelsea Finn OffRL 219 413 0 16 Feb 2021
A Finite Time Analysis of Two Time-Scale Actor Critic Methods Yue Wu Weitong Zhang Pan Xu Quanquan Gu 90 145 0 04 May 2020
Deep Reinforcement Learning for Autonomous Driving: A Survey B. R. Kiran Ibrahim Sobh V. Talpaert Patrick Mannion A. A. Sallab S. Yogamani P. Pérez 165 1,630 0 02 Feb 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016