SIERRA: A Modular Framework for Research Automation

TL;DR

SIERRA is a modular framework that streamlines the process of designing, executing, and analyzing experiments in intelligent systems research, enhancing reproducibility and customization across diverse platforms.

Contribution

It introduces a flexible, modular automation framework that simplifies experiment setup, execution, and result processing, improving reproducibility and adaptability for researchers.

Findings

Enables exact experiment replication across different environments.

Reduces manual scripting through automation and modular design.

Supports diverse platforms including HPC, robots, and simulators.

Abstract

Modern intelligent systems researchers employ the scientific method: they form hypotheses about system behavior, and then run experiments using one or more independent variables to test their hypotheses. We present SIERRA, a novel framework structured around that idea for accelerating research developments and improving reproducibility of results. SIERRA makes it easy to quickly specify the independent variable(s) for an experiment, generate experimental inputs, automatically run the experiment, and process the results to generate deliverables such as graphs and videos. SIERRA provides reproducible automation independent of the execution environment (HPC hardware, real robots, etc.) and targeted platform (arbitrary simulator or real robots), enabling exact experiment replication (up to the limit of the execution environment and platform). It employs a deeply modular approach that allows easy customization and extension of automation for the needs of individual researchers, thereby eliminating manual experiment configuration and result processing via throw-away scripts.