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..
What Can Learned Intrinsic Rewards Capture?
Authors: Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado Van Hasselt, David Silver, Satinder Singh
ICML 2020 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We present the results from our empirical investigations in two sections. We investigate these research questions in the grid-world domains illustrated in Figure 2. |
| Researcher Affiliation | Collaboration | 1University of Michigan 2Deep Mind. Correspondence to: Zeyu Zheng <EMAIL>, Junhyuk Oh <EMAIL>. |
| Pseudocode | Yes | Algorithm 1 Learning intrinsic rewards |
| Open Source Code | No | No explicit statement about providing open-source code or a link to a repository was found in the paper. |
| Open Datasets | No | We investigate these research questions in the grid-world domains illustrated in Figure 2. For each domain, we trained an intrinsic reward function across many lifetimes and evaluated it by training an agent using the learned reward. |
| Dataset Splits | No | No explicit mention of traditional training, validation, or test dataset splits (e.g., percentages or counts) was found, as the experiments involve interactive learning within simulated environments over lifetimes and episodes. |
| Hardware Specification | No | No specific hardware details (e.g., GPU/CPU models, memory) used for running experiments were mentioned in the main paper. |
| Software Dependencies | No | No specific software dependencies with version numbers were explicitly mentioned in the main text of the paper. |
| Experiment Setup | No | The details of implementation and hyperparameters are described in the supplementary material. |