Invariant Action Effect Model for Reinforcement Learning
Authors: Zheng-Mao Zhu, Shengyi Jiang, Yu-Ren Liu, Yang Yu, Kun Zhang9260-9268
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The extensive experiments on two benchmarks, i.e. Grid-World and Atari, show that the representations learned by IAEM preserve the invariance of action effects. Moreover, with the invariant action effect, IAEM can accelerate the learning process by 1.6x, rapidly generalize to new environments by finetuning on a few components, and outperform other dynamicsbased representation methods by 1.4x in limited steps. |
| Researcher Affiliation | Academia | 1 National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, China 2 Peng Cheng Laboratory, Shenzhen, Guangdong, China 3Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA, United States |
| Pseudocode | Yes | Algorithm 1: Invariant Action Effect Model (IAEM) |
| Open Source Code | No | The paper does not provide an explicit statement or a link to open-source code for the described methodology. |
| Open Datasets | Yes | We evaluate the performance, sample efficiency, and the generalization ability of IAEM on two widely-used benchmarks: Grid-World and Atari games. |
| Dataset Splits | No | The paper does not provide specific dataset split information (e.g., exact percentages, sample counts, or citations to predefined splits) for training, validation, and test sets. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., exact GPU/CPU models, processor types, or memory amounts) used for running its experiments. |
| Software Dependencies | No | For the network architecture in Atari, we use a state-of-the-art DQN baseline dopamine (Castro et al. 2018). (No specific version number for Dopamine or other key libraries is mentioned.) |
| Experiment Setup | Yes | Implementation details and hyperparameter values of IAEM are summarized in the appendix A. |