arXiv subjects

Ane Espeseth

Publications and source records attributed to Ane Espeseth.

2 recordsLinked to original sources

arXiv2026

The Affordance is the Message: Creative Media as Complex Systems

The affordances of a creative medium strongly condition the creative artefacts the medium will produce. In this work, we present a formalisation of computational creativity (CC) media using the conceptual toolbox of complex systems (CS). We introduce the notions of emergence, collective intelligence and self-organisation, non-linear dynamics, criticality, multi-scale hierarchy, phase transitions, diversity of attractors, path dependence, and open-endedness, and connect them to the existing CC literature. Together these nine properties form a vocabulary with which creative media can be described and compared at the system level, while medium affordances are the design-level mechanisms that determine each medium's complex system properties. The formalisation emphasises the influence of each medium's affordances in determining what the medium can produce in creative processes. To demonstrate the proposed theoretical approach, we characterise a diverse set of media (r/place, Minecraft, cellular automata, Twitter, Boids, ...) using this vocabulary. The proposed formalisation under the CS concepts serves a dual purpose: it establishes a link between the affordances and realised practices of the medium, and it offers a shared lens for characterising existing creative media.

cs.HC↗

arXiv2026

Conversable Complexity: Agentic LLM Collectives as Interpretable Substrates

Complexity and interpretability rarely coincide: systems rich enough for complex behaviours to emerge are usually too opaque to question, while transparent ones are too simple for anything complex to emerge. A single large language model (LLM) is a static artefact, hardly exhibiting any of the emergent properties we associate with life. This changes through interaction: populations of LLMs display emergent dynamics absent from isolated models. Furthermore, LLMs can be endowed with persistent memory, tools and shared skills, and the capacity to initiate actions unprompted, i.e., turning LLMs agentic. In this paper, we argue that such collectives of agents can serve as a computational substrate for Artificial Life (ALife) research. Critically, since the agents communicate in natural language, their collective behaviour can be directly interrogated by examining textual traces and asking the agents themselves. We outline the notion of interpretability in language-model research and extend it for collectives of agents. Lastly, we survey recent examples of agentic LLM collectives that already instantiate the idea of agentic substrates, from controlled experiments to deployments in the wild.

cs.CL↗