diff --git a/README.md b/README.md index 300e8e8..1a3bd05 100644 --- a/README.md +++ b/README.md @@ -5,27 +5,22 @@ This repository is associated with our 2019 GECCO extended abstract submission, Tag-accessed Memory for Genetic Programming. +Feel free to contact us with questions or file an issue on this repository if something +isn't clear! + **Navigation** -- [Todo](#todo) - [Project Overview](#project-overview) - [Tag-accessed Memory](#tag-accessed-memory) - [Contribution Authors](#contribution-authors) - [Repository Guide](#repository-guide) -- [Running the Experiment](#running-the-experiment) -- [Data Analyses](#data-analyses) +- [Supplemental Material](#supplemental-material) +- [References](#references) -## Todo - -- [ ] Document on experiment configurations -- [ ] Describe our experimental design -- [ ] Instruction set documentation -- [ ] Add copy of paper to repository - ## Project Overview We present an early exploration of tag-accessed memory for genetic programming. @@ -34,7 +29,7 @@ We present an early exploration of tag-accessed memory for genetic programming. Tags are evolvable labels that give genetic programs a flexible mechanism for specification. Tag-based naming schemes have been demonstrated for labeling and referencing program -modules [citations]. +modules (Spector, 2011; Lalejini and Ofria, 2018). We continue to expand the use of tags in GP by incorporating tag-based referencing into the memory model of a simple linear GP representation. @@ -53,7 +48,7 @@ setting the second register to the terminal value '2', multiplying the input by ### Contribution Authors -- [Alexander Lalejini](lalejini.com) +- [Alexander Lalejini](https://lalejini.com) - [Charles Ofria](https://scholar.google.com/citations?user=nYLuKDAAAAAJ&hl=en) ## Repository Guide @@ -62,7 +57,7 @@ setting the second register to the terminal value '2', multiplying the input by - Contains R scripts used for data analyses and generating graphs. - [data/](https://github.com/amlalejini/GECCO-2019-tag-accessed-memory/tree/master/data/) - Contains raw data for preliminary and published experiments as well as the - training and testing examples used for the programming synthesis benchmark + training and testing examples used for the programming synthesis benchmark problems (taken from [Tom Helmuth's example repository](https://github.com/thelmuth/Program-Synthesis-Benchmark-Data)). - [docs/](https://github.com/amlalejini/GECCO-2019-tag-accessed-memory/tree/master/docs/) - Contains miscellaneous documentation associated with this work. @@ -77,14 +72,18 @@ setting the second register to the terminal value '2', multiplying the input by - Contains utility scripts used for managing experiments on the HPCC and for aggregating and manipulating experiment data. -## Running the Experiment +## Supplemental Material -**Dependencies** +- Experiment configuration and GP system details: [./docs/gp-system.md](./docs/gp-system.md) +- Data analysis: Our analyses were done in R (R Core Team, 2016). + - Find a webpage (generated with R markdown) here: [http://lalejini.com/GECCO-2019-tag-accessed-memory/analysis/tag-mem-analysis.html](http://lalejini.com/GECCO-2019-tag-accessed-memory/analysis/tag-mem-analysis.html) + - Or, the Rmd file is here: [./analysis/tag-mem-analysis.Rmd](./analysis/tag-mem-analysis.Rmd) -- Empirical -- csv-parser +## References -## Data Analyses +Lalejini, A., & Ofria, C. (2018). Evolving event-driven programs with SignalGP. In Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO ’18 (pp. 1135–1142). New York, New York, USA: ACM Press. https://doi.org/10.1145/3205455.3205523 -Our analyses were done in R [cite]. [Find them here.](http://lalejini.com/GECCO-2019-tag-accessed-memory/analysis/tag-mem-analysis.html) +R Core Team (2016). R: A language and environment for statistical computing. R Foundation for +Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. +Spector, L., Martin, B., Harrington, K., & Helmuth, T. (2011). Tag-based modules in genetic programming. In Proceedings of the 13th annual conference on Genetic and evolutionary computation - GECCO ’11 (p. 1419). New York, New York, USA: ACM Press. https://doi.org/10.1145/2001576.2001767 \ No newline at end of file