:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Pleines, Marco, Addis, Daniel, Rubinstein, David, Zimmer, Frank, Preuss, Mike, Whidden, Peter
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2502.19920
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of Agents
by: Pleines, Marco, et al.
Published: (2023)

PokeRL: Reinforcement Learning for Pokemon Red
by: Mudireddy, Dheeraj, et al.
Published: (2026)

Human-Level Competitive Pokémon via Scalable Offline Reinforcement Learning with Transformers
by: Grigsby, Jake, et al.
Published: (2025)

In Trust We Survive: Emergent Trust Learning
by: Chen, Qianpu, et al.
Published: (2026)

Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization
by: Santoni, Maria Laura, et al.
Published: (2024)

Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning
by: Liu, Shijie, et al.
Published: (2025)

VGC-Bench: Towards Mastering Diverse Team Strategies in Competitive Pokémon
by: Angliss, Cameron, et al.
Published: (2025)

The Pokémon Theorem and other Fairness Impossibility Results
by: Smola, Daniel Matsui, et al.
Published: (2026)

Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning
by: Liu, Shijie, et al.
Published: (2025)

Rescaled Influence Functions: Accurate Data Attribution in High Dimension
by: Rubinstein, Ittai, et al.
Published: (2025)

Reinforcement Learning via Self-Distillation
by: Hübotter, Jonas, et al.
Published: (2026)

Parallel Sampling via Counting
by: Anari, Nima, et al.
Published: (2024)

Reinforcement Learning in POMDP's via Direct Gradient Ascent
by: Baxter, Jonathan, et al.
Published: (2025)

Global Safe Sequential Learning via Efficient Knowledge Transfer
by: Li, Cen-You, et al.
Published: (2024)

Adaptive Gain Scheduling using Reinforcement Learning for Quadcopter Control
by: Timmerman, Mike, et al.
Published: (2024)

Safe Active Learning for Gaussian Differential Equations
by: Glass, Leon, et al.
Published: (2024)

Interpreting Reinforcement Learning Agents with Susceptibilities
by: Elliott, Chris, et al.
Published: (2026)

Leveraging Reinforcement Learning in Red Teaming for Advanced Ransomware Attack Simulations
by: Wang, Cheng, et al.
Published: (2024)

Agentic Large Language Models, a survey
by: Plaat, Aske, et al.
Published: (2025)

Extracting Dynamical Models from Data
by: Zimmer, Michael F.
Published: (2021)

Comment on "Machine learning conservation laws from differential equations"
by: Zimmer, Michael F.
Published: (2024)

Harnessing intuitive local evolution rules for physical learning
by: Ezraty, Roie, et al.
Published: (2025)

Adaptive Data Analysis for Growing Data
by: Marchant, Neil G., et al.
Published: (2024)

Red-Team Multi-Agent Reinforcement Learning for Emergency Braking Scenario
by: Chen, Yinsong, et al.
Published: (2025)

PISmith: Reinforcement Learning-based Red Teaming for Prompt Injection Defenses
by: Yin, Chenlong, et al.
Published: (2026)

Safe Active Learning for Time-Series Modeling with Gaussian Processes
by: Zimmer, Christoph, et al.
Published: (2024)

Autonomous Assessment of Demonstration Sufficiency via Bayesian Inverse Reinforcement Learning
by: Trinh, Tu, et al.
Published: (2022)

RedRFT: A Light-Weight Benchmark for Reinforcement Fine-Tuning-Based Red Teaming
by: Zheng, Xiang, et al.
Published: (2025)

Approximating Latent Manifolds in Neural Networks via Vanishing Ideals
by: Pelleriti, Nico, et al.
Published: (2025)

Heterogeneous RBCs via Deep Multi-Agent Reinforcement Learning
by: Gabriele, Federico, et al.
Published: (2025)

Stagewise Reinforcement Learning and the Geometry of the Regret Landscape
by: Elliott, Chris, et al.
Published: (2026)

Online Symbolic Music Alignment with Offline Reinforcement Learning
by: Peter, Silvan David
Published: (2023)

On the Robustness of Distributed Machine Learning against Transfer Attacks
by: Andreina, Sébastien, et al.
Published: (2024)

Guaranteeing Control Requirements via Reward Shaping in Reinforcement Learning
by: De Lellis, Francesco, et al.
Published: (2023)

Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging
by: Zimmer, Max, et al.
Published: (2023)

AttackGNN: Red-Teaming GNNs in Hardware Security Using Reinforcement Learning
by: Gohil, Vasudev, et al.
Published: (2024)

Amortized Active Learning for Nonparametric Functions
by: Li, Cen-You, et al.
Published: (2024)

RECON: Robust symmetry discovery via Explicit Canonical Orientation Normalization
by: Urbano, Alonso, et al.
Published: (2025)

Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
by: Jiralerspong, Marco, et al.
Published: (2025)

Offline Hierarchical Reinforcement Learning via Inverse Optimization
by: Schmidt, Carolin, et al.
Published: (2024)