# Particularity

arXiv: https://arxiv.org/abs/2306.06812 · HTML: https://mlsanity.com/paper/2306.06812/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 41 references that are in the map.
- First posted on arXiv 12 Jun 2023.

## Builds on (most cited first, 15 of 15)

- [Illuminating search spaces by mapping elites](https://mlsanity.com/paper/1504.04909/) (2015)
- [Where are we now? A large benchmark study of recent symbolic regression methods](https://mlsanity.com/paper/1804.09331/) (2018)
- [Epsilon-Lexicase Selection for Regression](https://mlsanity.com/paper/1905.13266/) (2019)
- [PSB2: The Second Program Synthesis Benchmark Suite](https://mlsanity.com/paper/2106.06086/) (2021)
- [Lexicase selection in Learning Classifier Systems](https://mlsanity.com/paper/1907.04736/) (2019)
- [Problem-solving benefits of down-sampled lexicase selection](https://mlsanity.com/paper/2106.06085/) (2021)
- [Lexicase Selection at Scale](https://mlsanity.com/paper/2208.10719/) (2022)
- [Informed Down-Sampled Lexicase Selection: Identifying productive training cases for efficient problem solving](https://mlsanity.com/paper/2301.01488/) (2023)
- [Calculating lexicase selection probabilities is NP-Hard](https://mlsanity.com/paper/2301.06724/) (2023)
- [Probabilistic Lexicase Selection](https://mlsanity.com/paper/2305.11681/) (2023)
- [A Static Analysis of Informed Down-Samples](https://mlsanity.com/paper/2304.01978/) (2023)
- [The Environmental Discontinuity Hypothesis for Down-Sampled Lexicase Selection](https://mlsanity.com/paper/2205.15931/) (2022)
- [Untangling the Effects of Down-Sampling and Selection in Genetic Programming](https://mlsanity.com/paper/2304.07089/) (2023)
- [Can the Problem-Solving Benefits of Quality Diversity Be Obtained Without Explicit Diversity Maintenance?](https://mlsanity.com/paper/2305.07767/) (2023)
- [Improving Recommendation System Serendipity Through Lexicase Selection](https://mlsanity.com/paper/2305.11044/) (2023)

## Built on by (most cited first, 3 of 3)

- [Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization](https://mlsanity.com/paper/2310.12103/) (2023)
- [Vector Policy Optimization: Training for Diversity Improves Test-Time Search](https://mlsanity.com/paper/2605.22817/) (2026)
- [DALex: Lexicase-like Selection via Diverse Aggregation](https://mlsanity.com/paper/2401.12424/) (2024)

## Abstract (arXiv)

We describe a design principle for adaptive systems under which adaptation is driven by particular challenges that the environment poses, as opposed to average or otherwise aggregated measures of performance over many challenges. We trace the development of this "particularity" approach from the use of lexicase selection in genetic programming to "particularist" approaches to other forms of machine learning and to the design of adaptive systems more generally.