Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs
Authors: Himanshu Sahni, Toby Buckley, Pieter Abbeel, Ilya Kuzovkin
NeurIPS 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We validate our approach on 3D navigation tasks and a simulated robotics application and show marked improvement over baselines derived from previous work. 6 Experiments We test our method on two first person visual environments. In a modified version of Mini World [6], we design two tasks. |
| Researcher Affiliation | Collaboration | Himanshu Sahni Toby Buckley Pieter Abbeel , Ilya Kuzovkin Georgia Institute of Technology Off World Inc. University of California, Berkeley Work done as an intern at Off World Inc. Correspondence to: hsahni3@gatech.edu |
| Pseudocode | Yes | Algorithm 1 HALGAN+HER |
| Open Source Code | No | The paper does not provide a direct link or explicit statement about the availability of its source code. |
| Open Datasets | No | HALGAN is trained on a dataset, R, of observations of the goal where the relative configuration to the agent is known. For the purposes of our experiments, we collect the training data in R by using the last 16 or 32 states of a successful rollout. The paper describes generating its own dataset within open environments but does not provide access to the collected dataset itself. |
| Dataset Splits | No | The paper describes data collection and training processes but does not specify explicit train/validation/test dataset splits with percentages, counts, or references to predefined splits. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., GPU models, CPU types, memory) used for running the experiments. |
| Software Dependencies | No | The paper mentions software like 'Mini World', 'Gazebo', 'gym-gazebo', 'DDQN', and 'DDPG' but does not provide specific version numbers for these or any other software dependencies. |
| Experiment Setup | No | Details of all experimental hyperparameters are provided in the appendix. This indicates that specific setup details are not present in the main text of the paper. |