---
abstract: 'Inspired by recent work of Fink, Reeves, Palma and Farr [@Fink-RPF-2016arxiv] on innovation in language, gastronomy, and technology, I study how new symbol discovery manifests itself in terms of additional “word” vocabulary being available from dictionaries generated from a finite number of symbols. Several distinct dictionary generation models are investigated using numerical simulation, with emphasis on the scaling of knowledge as dictionary generators and parameters are varied, and the role of which order the symbols are discovered in.'
author:
- Paul Kinsler
bibliography:
- '../../bibtex.bib'
title: |
    Stylized innovation:\
    interrogating incrementally available randomised dictionaries
---

Introduction {#S-Introduction}
============

Fink et al. [@Fink-RPF-2016arxiv] recently presented an interesting discussion and analysis of serendipity and strategy in innovation scenarios, paying particular attention to real-world datasets based on language, gastronomy, and technology. Here, however, I take a look at the same type of innovation/discovery processes in the context of synthetic datasets where I have designed a range of different underlying “innovation” spaces to investigate. Although this is clearly not as realistic as using real-world datasets, it allows us to (a) try to establish both individual and universal features of a discovery/innovation process, and (b) avoids us having to make ad hoc judgments 