A Minimalist Approach to Offline Reinforcement Learning

von Fujimoto, Scott
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 24 of 36 (2022)

Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters

von Ghasemipour, Kamyar
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 24 of 50 (2023)

EMAQ: EXPECTED-MAX Q-LEARNING OPERATOR FOR SIMPLE YET EFFECTIVE OFFLINE AND ONLINE RL

von GHASEMIPOUR, SEYED KAMYAR SEYED
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 5 of 16 (2022)

Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning

von Furuta, Hiroki
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 12 of 36 (2022)

Why Should I Trust You, Bellman? the Bellman Error is a Poor Replacement for Value Error

von Fujimoto, Scott
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 9 of 33 (2023)

VARIATIONAL EMPOWERMENT AS REPRESENTATION LEARNING FOR GOAL-BASED REINFORCEMENT LEARNING

von CHOI, JONGWOOK
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 3 of 16 (2022)

Large Language Models are Zero-Shot Reasoners

von Kojima, Takeshi
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 29 of 50 (2023)

POLICY INFORMATION CAPACITY: INFORMATION-THEORETIC MEASURE FOR TASK COMPLEXITY IN DEEP REINFORCEMENT LEARNING

von FURUTA, HIROKI
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 5 of 16 (2022)

Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning

von Ghasemipour, Seyed Kamyar Seyed
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 9 of 33 (2023)