BadRL: Sparse Targeted Backdoor Attack against Reinforcement Learning
Authors: Jing Cui, Yufei Han, Yuzhe Ma, Jianbin Jiao, Junge Zhang
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Empirical results on various classic RL tasks illustrate that Bad RL can substantially degrade the performance of a victim agent with minimal poisoning efforts (0.003% of total training steps) during training and infrequent attacks during testing. Code is available at: https://github.com/7777777cc/code. |
| Researcher Affiliation | Collaboration | Jing Cui1, Yufei Han2, Yuzhe Ma3, Jianbin Jiao1, Junge Zhang4,1* 1University of Chinese Academy of Sciences 2INRIA 3Microsoft Azure AI 4Institute of Automation, Chinese Academy of Sciences |
| Pseudocode | Yes | Algorithm 1: Bad RL Algorithm |
| Open Source Code | Yes | Code is available at: https://github.com/7777777cc/code. |
| Open Datasets | Yes | Empirical results on various classic RL tasks illustrate that Bad RL can substantially degrade the performance of a victim agent... Empirical evaluations on four classic RL tasks reveal that Bad RL-based backdoor attacks... Pong, Breakout, Qbert, Space Invaders |
| Dataset Splits | No | The paper describes 'poisoning proportion: 0.003%, 0.003%, 0.002%, 0.002% for Pong, Breakout, Qbert, Space Invaders' as part of the training effort but does not specify dataset splits (e.g., train/validation/test percentages or counts) for reproducibility. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies or library versions (e.g., Python version, PyTorch version, etc.) needed to replicate the experiment. |
| Experiment Setup | Yes | Poisoning proportion: 0.003%, 0.003%, 0.002%, 0.002% for Pong, Breakout, Qbert, Space Invaders. Models are tested every 10000 steps. |