Asynchronous Coagent Networks
Authors: James Kostas, Chris Nota, Philip Thomas
ICML 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The contributions of this paper are: 3) empirical support of our theoretical claims regarding the gradients of asynchronous CPGAs, and 4) a proof that asynchronous CPGAs generalize the option-critic framework |
| Researcher Affiliation | Academia | 1College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, USA. Correspondence to: James E. Kostas <jekostas@umass.edu>. |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described. |
| Open Datasets | No | The paper refers to empirical tests and figures in the supplementary material (Section D) but does not provide any specific public dataset names, links, or citations for the data used in these tests. |
| Dataset Splits | No | The paper does not provide specific dataset split information (e.g., percentages, sample counts, or predefined splits) for training, validation, or testing. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers. |
| Experiment Setup | No | The paper does not contain specific experimental setup details, hyperparameters, or training configurations in the main text. |