Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Policy Optimization with Demonstrations
Authors: Bingyi Kang, Zequn Jie, Jiashi Feng
ICML 2018 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We show that POf D induces implicit dynamic reward shaping and brings provable bene๏ฌts for policy improvement. Furthermore, it can be combined with policy gradient methods to produce state-of-the-art results, as demonstrated experimentally on a range of popular benchmark sparse-reward tasks, even when the demonstrations are few and imperfect. |
| Researcher Affiliation | Collaboration | 1Department of Electrical and Computer Engineering, National University of Singapore, Singapore 2Tencent AI Lab, China. |
| Pseudocode | Yes | Algorithm 1 Policy optimization with demonstrations |
| Open Source Code | No | The paper does not provide an explicit statement or link for open-source code for its methodology. |
| Open Datasets | Yes | To comprehensively assess our method, we conduct extensive experiments on eight widely used physical control tasks, ranging from low-dimensional ones such as cartpole (Barto et al., 1983) and mountain car (Moore, 1990) to high-dimensional and naturally sparse environments based on Open AI Gym (Brockman et al., 2016) and Mujoco (Todorov et al., 2012). |
| Dataset Splits | No | The paper mentions using |
| Hardware Specification | No | The paper does not provide specific details about the hardware used to run the experiments. |
| Software Dependencies | No | Implementation Details Due to space limit, we defer implementation details to the supplementary material. |
| Experiment Setup | No | Implementation Details Due to space limit, we defer implementation details to the supplementary material. |