Evolutionary Innovations and Where to Find Them: Routes to Open-Ended Evolution in Natural and Artificial Systems
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Abstract (arXiv)
This paper presents a high-level conceptual framework to help orient the discussion and implementation of open-endedness in evolutionary systems. Drawing upon earlier work by Banzhaf et al., three different kinds of open-endedness are identified: exploratory, expansive, and transformational. These are characterised in terms of their relationship to the search space of phenotypic behaviours. A formalism is introduced to describe three key processes required for an evolutionary process: the generation of a phenotype from a genetic description, the evaluation of that phenotype, and the reproduction with variation of individuals according to their evaluation. The distinction is made between intrinsic and extrinsic implementations of these processes. A discussion then investigates how various interactions between these processes, and their modes of implementation, can lead to open-endedness. However, an important contribution of the paper is the demonstration that these considerations relate to exploratory open-endedness only. Conditions for the implementation of the more interesting kinds of open-endedness - expansive and transformational - are also discussed, emphasizing factors such as multiple domains of behaviour, transdomain bridges, and non-additive compositional systems. These factors relate not to the generic evolutionary properties of individuals and populations, but rather to the nature of the building blocks out of which individual organisms are constructed, and the laws and properties of the environment in which they exist. The paper ends with suggestions of how the framework can be used to categorise and compare the open-ended evolutionary potential of different systems, how it might guide the design of systems with greater capacity for open-ended evolution, and how it might be further improved.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Jun 2018.
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Citing papers per year: 2022: 3; 2023: 1; 2024: 3; 2025: 3.
10 papers.
- 2025Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesiscited by 19
- 2022Open-Ended Evolution for Minecraft Building Generationcited by 9
- 2025ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamworkcited by 6
- 2023On the Unexpected Abilities of Large Language Modelscited by 5
- 2022Evolved Open-Endedness in Cultural Evolution: A New Dimension in Open-Ended Evolution Researchcited by 3
- 2025On Improvisation and Open-Endedness: Insights for Experiential AIcited by 2
- 2022Towards the Neuroevolution of Low-level Artificial General Intelligencecited by 1
- 2024On Creativity and Open-Endednesscited by 1
- 2024Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospectscited by 1
- 2024The use of knowledge in open-ended systemscited by 0
- 2025On Improvisation and Open-Endedness: Insights for Experiential AI1 Nov 2025
- 2025ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamwork29 May 2025
- 2025Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesis16 May 2025
- 2024The use of knowledge in open-ended systems13 Nov 2024
- 2024Evolutionary Computation for the Design and Enrichment of General-Purpose Artificial Intelligence Systems: Survey and Prospects3 Jun 2024
- 2024On Creativity and Open-Endedness28 May 2024
- 2023On the Unexpected Abilities of Large Language Models9 Aug 2023
- 2022Open-Ended Evolution for Minecraft Building Generation7 Sep 2022
- 2022Towards the Neuroevolution of Low-level Artificial General Intelligence27 Jul 2022
- 2022Evolved Open-Endedness in Cultural Evolution: A New Dimension in Open-Ended Evolution Research24 Mar 2022