Saved in:
| Main Author: | Ollivier, Yann |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.10792 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Which Features are Best for Successor Features?
by: Ollivier, Yann
Published: (2025)
by: Ollivier, Yann
Published: (2025)
Simple Ingredients for Offline Reinforcement Learning
by: Cetin, Edoardo, et al.
Published: (2024)
by: Cetin, Edoardo, et al.
Published: (2024)
On Zero-Shot Reinforcement Learning
by: Jeen, Scott
Published: (2025)
by: Jeen, Scott
Published: (2025)
Finer Behavioral Foundation Models via Auto-Regressive Features and Advantage Weighting
by: Cetin, Edoardo, et al.
Published: (2024)
by: Cetin, Edoardo, et al.
Published: (2024)
An Equivalence between Bayesian Priors and Penalties in Variational Inference
by: Wolinski, Pierre, et al.
Published: (2020)
by: Wolinski, Pierre, et al.
Published: (2020)
A Unified Framework for Zero-Shot Reinforcement Learning
by: Di Ventura, Jacopo, et al.
Published: (2025)
by: Di Ventura, Jacopo, et al.
Published: (2025)
Tackling Data Heterogeneity in Federated Learning via Loss Decomposition
by: Zeng, Shuang, et al.
Published: (2024)
by: Zeng, Shuang, et al.
Published: (2024)
Towards Robust Zero-Shot Reinforcement Learning
by: Zheng, Kexin, et al.
Published: (2025)
by: Zheng, Kexin, et al.
Published: (2025)
Provable Zero-Shot Generalization in Offline Reinforcement Learning
by: Wang, Zhiyong, et al.
Published: (2025)
by: Wang, Zhiyong, et al.
Published: (2025)
Zero-Shot Reinforcement Learning Under Partial Observability
by: Jeen, Scott, et al.
Published: (2025)
by: Jeen, Scott, et al.
Published: (2025)
Zero-Shot Reinforcement Learning via Function Encoders
by: Ingebrand, Tyler, et al.
Published: (2024)
by: Ingebrand, Tyler, et al.
Published: (2024)
TD-JEPA: Latent-predictive Representations for Zero-Shot Reinforcement Learning
by: Bagatella, Marco, et al.
Published: (2025)
by: Bagatella, Marco, et al.
Published: (2025)
Efficient Reinforcement Learning for Zero-Shot Coordination in Evolving Games
by: Hui, Bingyu, et al.
Published: (2025)
by: Hui, Bingyu, et al.
Published: (2025)
Zero-Shot Reinforcement Learning from Low Quality Data
by: Jeen, Scott, et al.
Published: (2023)
by: Jeen, Scott, et al.
Published: (2023)
Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation
by: Zhang, Wanpeng, et al.
Published: (2023)
by: Zhang, Wanpeng, et al.
Published: (2023)
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings
by: Frans, Kevin, et al.
Published: (2024)
by: Frans, Kevin, et al.
Published: (2024)
Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning
by: Rocamonde, Juan, et al.
Published: (2023)
by: Rocamonde, Juan, et al.
Published: (2023)
Few-Shot Inspired Generative Zero-Shot Learning
by: Shohag, Md Shakil Ahamed, et al.
Published: (2025)
by: Shohag, Md Shakil Ahamed, et al.
Published: (2025)
Zero-Shot Policy Transfer in Reinforcement Learning using Buckingham's Pi Theorem
by: Pascoa, Francisco, et al.
Published: (2025)
by: Pascoa, Francisco, et al.
Published: (2025)
Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization
by: Marton, Sascha, et al.
Published: (2024)
by: Marton, Sascha, et al.
Published: (2024)
A Zero-Shot Reinforcement Learning Strategy for Autonomous Guidewire Navigation
by: Scarponi, Valentina, et al.
Published: (2024)
by: Scarponi, Valentina, et al.
Published: (2024)
Adaptive Few-Shot Learning (AFSL): Tackling Data Scarcity with Stability, Robustness, and Versatility
by: Agrawal, Rishabh
Published: (2025)
by: Agrawal, Rishabh
Published: (2025)
Inferring Behavior-Specific Context Improves Zero-Shot Generalization in Reinforcement Learning
by: Ndir, Tidiane Camaret, et al.
Published: (2024)
by: Ndir, Tidiane Camaret, et al.
Published: (2024)
Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning
by: Zhang, Chi, et al.
Published: (2025)
by: Zhang, Chi, et al.
Published: (2025)
Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
by: Xu, Jiawei, et al.
Published: (2024)
by: Xu, Jiawei, et al.
Published: (2024)
PREDILECT: Preferences Delineated with Zero-Shot Language-based Reasoning in Reinforcement Learning
by: Holk, Simon, et al.
Published: (2024)
by: Holk, Simon, et al.
Published: (2024)
FedKL: Tackling Data Heterogeneity in Federated Reinforcement Learning by Penalizing KL Divergence
by: Xie, Zhijie, et al.
Published: (2022)
by: Xie, Zhijie, et al.
Published: (2022)
Zero-Shot Robustification of Zero-Shot Models
by: Adila, Dyah, et al.
Published: (2023)
by: Adila, Dyah, et al.
Published: (2023)
DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design
by: Garcin, Samuel, et al.
Published: (2024)
by: Garcin, Samuel, et al.
Published: (2024)
Maximum Entropy Behavior Exploration for Sim2Real Zero-Shot Reinforcement Learning
by: Hu, Jiajun, et al.
Published: (2026)
by: Hu, Jiajun, et al.
Published: (2026)
Reinforcement Learning with Physics-Informed Symbolic Program Priors for Zero-Shot Wireless Indoor Navigation
by: Li, Tao, et al.
Published: (2025)
by: Li, Tao, et al.
Published: (2025)
Zero-Shot Learning for Obsolescence Risk Forecasting
by: Saad, Elie, et al.
Published: (2025)
by: Saad, Elie, et al.
Published: (2025)
Soft Tokens, Hard Truths
by: Butt, Natasha, et al.
Published: (2025)
by: Butt, Natasha, et al.
Published: (2025)
Zero-Shot Off-Policy Learning
by: Asadulaev, Arip, et al.
Published: (2026)
by: Asadulaev, Arip, et al.
Published: (2026)
Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability
by: Sundaram, Shobhita, et al.
Published: (2026)
by: Sundaram, Shobhita, et al.
Published: (2026)
Heterogeneous Multi-Agent Reinforcement Learning for Zero-Shot Scalable Collaboration
by: Guo, Xudong, et al.
Published: (2024)
by: Guo, Xudong, et al.
Published: (2024)
A Minimalist Prompt for Zero-Shot Policy Learning
by: Song, Meng, et al.
Published: (2024)
by: Song, Meng, et al.
Published: (2024)
Tackling GNARLy Problems: Graph Neural Algorithmic Reasoning Reimagined through Reinforcement Learning
by: Schutz, Alex, et al.
Published: (2025)
by: Schutz, Alex, et al.
Published: (2025)
Tackling Uncertainties in Multi-Agent Reinforcement Learning through Integration of Agent Termination Dynamics
by: Hazra, Somnath, et al.
Published: (2025)
by: Hazra, Somnath, et al.
Published: (2025)
Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contexts
by: Chapman, James, et al.
Published: (2025)
by: Chapman, James, et al.
Published: (2025)
Similar Items
-
Which Features are Best for Successor Features?
by: Ollivier, Yann
Published: (2025) -
Simple Ingredients for Offline Reinforcement Learning
by: Cetin, Edoardo, et al.
Published: (2024) -
On Zero-Shot Reinforcement Learning
by: Jeen, Scott
Published: (2025) -
Finer Behavioral Foundation Models via Auto-Regressive Features and Advantage Weighting
by: Cetin, Edoardo, et al.
Published: (2024) -
An Equivalence between Bayesian Priors and Penalties in Variational Inference
by: Wolinski, Pierre, et al.
Published: (2020)